647 jobs found

Owns moderately complex components within Compute/Imaging platform services; leads team-level improvements to integration frameworks and developer tooling. Performs deep debugging across a bounded set of Operating System, Infrastructure Orchestration, distributed services, driving fixes that protect downstream consumers and upgrade paths. Analyzes usage, performance, and error budgets for specific platform surfaces; implements targeted resilience and capacity optimizations. Authors and curates team-scoped documentation, samples, and adoption guidance. Designs, implements, and optimizes components in distributed systems with an emphasis on scalability, resiliency, and operability. Delivers features and load/performance tests; leverages data plane platforms and distributed state tools for high-volume retrieval, storage, and processing; and reviews peers' implementations for scalability compliance. Builds fault-tolerant paths (redundancy, replication, automatic failover), applies recovery oriented principles, and implements retries, circuit breakers, and timeouts. Proactively detects and mitigates issues via tests, alarms, dashboards, and telemetry; authors runbooks and participates in incident response and RCAs. Implements standard replication and synchronization, develops automation/IaC for troubleshooting and maintenance, and applies advanced security controls (encryption, access, remediation) while ensuring change, compliance, and documentation standards are met. Responsibilities Key Responsibilities Platform Software Development: Own a bounded Compute/Imaging platform component (service module area) and evolve its contracts for multi-tenant use. Perform deep debugging across a limited-service graph; drive compatibility-safe remediation plans. Implement targeted resilience/capacity patterns and document adoption guidance for team consumers. Software Development and Coding - Design, Testing, and Optimization: Designs software solutions and analyzes and helps identify requirements to achieve business and operational goals, independently. Adheres to and suggests improvements to all phases of the software development lifecycle. Utilizes working knowledge to develop new software features and enhancements following design specifications and develops documents to clarify software design and code. Leads code reviews in designated areas to help drive improvements. Conducts debugging and troubleshooting to identify and fix moderately complex software issues. Develops fixes for identified issues. Implements software testing (e.g., functional and non-functional testing), quality assurance processes, software error logging, monitoring, and observability for effective debugging, ensuring review by manager and/or lead throughout the process. Exercises judgment and discretion to conduct performance profiling and optimization of coding. Troubleshoots and resolves moderately complex issues related to application programming interface (API) functionality and integration. Implements moderately complex API versioning, lifecycle, and interoperability strategies. Software Architecture - Software System Structural Design: Designs and develops software, systems, and services aligned to pre-defined system architecture. Develops working knowledge of software architecture decisions and best practices. Collaborates with team leads to review work to ensure alignment with software architecture. Implements moderately complex performance optimization and scalability strategies in software design. Issue/Defect Collaboration - Software Products Support: Collaborates within and beyond immediate team to understand customer issues and align solutions. May provide technical guidance and support to customers regarding customer-reported issues, independently. Coaches, mentors, and guides others to advocate for customers' interests and suggests product enhancements based on feedback. Influences team to ensure customer satisfaction through timely resolution of issues and effective communication. Implements customer issue and/or defect handling and training processes, independently. Investigates and troubleshoots complex product maintenance issues to ensure customer agreement on short- and long-term solutions (e.g., future enhancements). Practices and Standards Compliance - Security and Compliance: Collaborates with the team to establish and follow development practices and coding standards. Exercises judgment and discretion to ensure code quality and adherence to broad acceptance criteria during development. Keeps up to date with industry best practices and applies them to software development processes. Implements secure coding practices to prevent security vulnerabilities. Development Operations - System Maintenance: Performs periodic maintenance and testing operations for systems that require upgrading or patching (e.g., for critical vulnerabilities). Exercises judgment and discretion to drive improvements, ensure automation, testing, and debugging of systems to ensure service/product availability, health, support, and reliability. Participate in Teams Oncall Rotations to provide reactive support for team's service area for critical incidents recovery. Core Responsibilities Planning & Execution: Independently manages work, monitoring timelines and deliverables to ensure projects or initiatives stay on track and meet requirements. Proactively prioritizes work and adapts to resource or timeline shifts, suggesting adjustments to maintain project efficiency. Collaboration & Partnership: Collaborates across teams to align on expectations and achieve shared objectives. Builds and maintains a comprehensive understanding of business, stakeholder, and/or customer needs to build and support effective partnerships. Actively listens to diverse perspectives and asks questions to ensure understanding of others. Problem Solving: Independently identifies and addresses standard and non-standard issues in accordance with standard practices, escalating more complex issues as appropriate. Analyzes data and/or information from multiple sources to troubleshoot standard and non-standard errors. Contributes to knowledge sharing and best practices. Continuous Learning: Embraces continuous learning by actively seeking to build knowledge and new skills and/or tools and staying current with industry trends and best practices. Seeks out and leverages feedback and training to improve skills. Contributes to a culture of continuous learning and knowledge sharing with team members. Continuous Improvement: Develops ideas and recommends updates to increase the efficiency and effectiveness of processes, protocols, and workflows within a team. Seeks input from team members on alternative approaches and methods for improving work. Requirements 5+ years' experience delivering and operating large scale, highly available distributed systems. Strong knowledge and interest in AI adoption including prompt engineering and agentic programming, with ChatGPT and Codex experience a plus. Strong knowledge of a base language such as Java, with a preference for functional programming language such as Scala. Strong knowledge of data structures, algorithms, operating systems, and distributed systems fundamentals. Experience with tools such as Terraform for Infrastructure as Code. Deep knowledge with networking protocols (TCP/IP, HTTP) and network architectures. Ability to design, troubleshoot and maintain networking infrastructure for high throughput use cases. Strong understanding of databases, storage, and distributed persistence technologies. Strong troubleshooting and performance tuning skills. Experience building multi-tenant, virtualized infrastructure a strong plus. Qualifications Disclaimer: Certain U.S. based or U.S. customer or client-facing roles may be required to comply with applicable requirements, such as immunization/occupational health mandates, and/or drug testing requirements. Range and benefit information provided in this posting are specific to the stated locations only US: Hiring Range in USD from: $92,500 to $209,500 per annum. May be eligible for bonus and equity. Oracle maintains broad salary ranges for its roles in order to account for variations in knowledge, skills, experience, market conditions and locations, as well as reflect Oracle's differing products, industries and lines of business. Candidates are typically placed into the range based on the preceding factors as well as internal peer equity. Oracle US offers a comprehensive benefits package which includes the following: 1. Medical, dental, and vision insurance, including expert medical opinion 2. Short term disability and long term disability 3. Life insurance and AD&D 4. Supplemental life insurance (Employee/Spouse/Child) 5. Health care and dependent care Flexible Spending Accounts 6. Pre-tax commuter and parking benefits 7. 401(k) Savings and Investment Plan with company match 8. Paid time off: Flexible Vacation is provided to all eligible employees assigned to a salaried (non-overtime eligible) position. Accrued Vacation is provided to all other employees eligible for vacation benefits. For employees working at least 35 hours per week . click apply for full job details

Implements and optimizes components within existing distributed systems under guidance. Applies basic scalability requirements, conducts performance/load testing, and configures resiliency features (retries, circuit breakers, timeouts) to handle network variability. Builds telemetry, alerts, and runbook-driven procedures; delivers scoped features and fault-injection tests; and helps implement basic data replication and synchronization. Assists with on-call rotations, uses automation/IaC scripts to troubleshoot, and follows change, security, and compliance procedures (encryption, access controls, remediation plans) while escalating complex issues to senior engineers. Responsibilities Responsibilities As a Core Infrastructure Software Engineer, you will: Design, develop, and operate highly available, scalable, and fault-tolerant microservices across control plane, connectivity, distributed-systems data plane, and Linux daemon technologies. Contribute throughout the product lifecycle, from conceptualization and product definition through design, development, launch, and operational maturity. Identify opportunities to automate engineering workflows across development, testing, troubleshooting, operations, and documentation, leveraging AI-assisted and agentic approaches where appropriate. Measure and improve reliability, delivery velocity, operational efficiency, customer outcomes, and engineering productivity, while sharing effective practices across the team. You should be a hands-on, adaptable, and self-motivated engineer who learns quickly, applies new tools thoughtfully, and enjoys solving challenging high-availability and scalability problems. Qualifications 3+ years of experience with systems or application development. 3+ years of experience with distributed systems or backend development. Bachelor's degree in Computer Science or a related engineering field. Proficiency with data structures, algorithms, and operating systems. Experience with distributed systems, including familiarity with CAP theorem, consensus, messaging, and high availability. Demonstrated willingness to learn and responsibly apply AI/LLM tools, skills, and automation to improve engineering workflows. Qualifications Disclaimer: Certain U.S. based or U.S. customer or client-facing roles may be required to comply with applicable requirements, such as immunization/occupational health mandates, and/or drug testing requirements. Range and benefit information provided in this posting are specific to the stated locations only US: Hiring Range in USD from: $70,000 to $166,100 per annum. May be eligible for bonus and equity. Oracle maintains broad salary ranges for its roles in order to account for variations in knowledge, skills, experience, market conditions and locations, as well as reflect Oracle's differing products, industries and lines of business. Candidates are typically placed into the range based on the preceding factors as well as internal peer equity. Oracle US offers a comprehensive benefits package which includes the following: 1. Medical, dental, and vision insurance, including expert medical opinion 2. Short term disability and long term disability 3. Life insurance and AD&D 4. Supplemental life insurance (Employee/Spouse/Child) 5. Health care and dependent care Flexible Spending Accounts 6. Pre-tax commuter and parking benefits 7. 401(k) Savings and Investment Plan with company match 8. Paid time off: Flexible Vacation is provided to all eligible employees assigned to a salaried (non-overtime eligible) position. Accrued Vacation is provided to all other employees eligible for vacation benefits. For employees working at least 35 hours per week, the vacation accrual rate is 13 days annually for the first three years of employment and 18 days annually for subsequent years of employment. Vacation accrual is prorated for employees working between 20 and 34 hours per week. Employees working fewer than 20 hours per week are not eligible for vacation. 9. 11 paid holidays 10. Paid sick leave: 72 hours of paid sick leave upon date of hire. Refreshes each calendar year. Unused balance will carry over each year up to a maximum cap of 112 hours. 11. Paid parental leave 12. Adoption assistance 13. Employee Stock Purchase Plan 14. Financial planning and group legal 15. Voluntary benefits including auto, homeowner and pet insurance The role will generally accept applications for at least three calendar days from the posting date or as long as the job remains posted. As part of Oracle's onboarding process and consistent with applicable law, US-based employees are required to complete identity verification, which involves the collection and processing of their biometric information. Accommodations to this requirement may be granted following an individualized assessment. Only Oracle brings together the data, infrastructure, applications, and expertise to power everything from industry innovations to life-saving care. And with AI embedded across our products and services, we help customers turn that promise into a better future for all. Discover your potential at a company leading the way in AI and cloud solutions that impact billions of lives. True innovation starts when everyone is empowered to contribute. That's why we're committed to growing a workforce that promotes opportunities for all with competitive benefits that support our people with flexible medical, life insurance, and retirement options. We also encourage employees to give back to their communities through our volunteer programs. We're committed to including people with disabilities at all stages of the employment process. If you require accessibility assistance or accommodation for a disability at any point, let us know by emailing or by calling 1- in the United States. Oracle is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability and protected veterans' status, or any other characteristic protected by law. Oracle will consider for employment qualified applicants with arrest and conviction records pursuant to applicable law.

Compute & GPU Provisioning: Experience with BIOS/UEFI, BMC/SMM, Redfish, PLDM, TPM, virtual media, firmware installation and upgrades, and hardware lifecycle management. CPU/GPU & Hardware Systems: Knowledge of CPU/GPU architectures, PCIe, DMA, NICs, NVMe, device enumeration, hardware bring-up, burn-in validation, and firmware debugging. Bare-Metal & OS Provisioning: Experience with PXE/iPXE, DHCP/DNS, Linux networking, OS imaging, and secure fleet-scale provisioning and automation. Leads development and begins architecting scalable, container-based services that build, validate, and monitor liquid-cooled GPU infrastructure across factory environments. Develops secure infrastructure, control-plane workflows, and data-plane test capabilities that orchestrate manufacturing test lifecycles, operator workflows, quality gates, fleet status, and business reporting for platforms including GB200, GB300, VR, MI355, and MI455. Automates and maintains GPU test validation; manages consistent firmware, software, and hardware configuration; and develops repair and triage capabilities that identify root causes and guide recovery. Partners with Supply Chain Operations, Hardware Development, external manufacturing partners, data-center operations, NVIDIA, and AMD to resolve issues before racks ship. Establishes manufacturing yield, throughput, quality, and deployment-readiness metrics that reduce rework and downstream failures, improve data-center ingestion, and accelerate reliable hyperscale AI infrastructure delivery. Responsibilities Responsibilities Lead the design, implementation, and ongoing evolution of core distributed systems and data-plane services at hyperscale. Define scalability, elasticity, durability, and availability requirements for owned components and ensure designs meet them. Optimize high-throughput data paths for large-scale retrieval, storage, and processing using distributed state, replication, and synchronization patterns. Design fault-tolerant systems that support in-service updates through redundancy, automatic failover, and recovery-oriented design. Apply sound distributed-systems tradeoffs for network partitions and reliability, including load shedding, throttling, rate limiting, retries, and timeouts. Establish service-level objectives, key performance indicators, telemetry, dashboards, and proactive alerting for critical systems. Design and lead performance, load, fault-injection, and brownout testing to validate correctness, resilience, and operational readiness. Lead production incident diagnosis and recovery, guide root-cause analysis, and mentor engineers in operational excellence. Build and improve Infrastructure as Code and operational automation that enable safe patching, updates, rollbacks, and change management. Apply robust security controls and remediation practices for multi-tenant cloud infrastructure, including encryption, access controls, and compliance readiness. Qualifications Bachelor's or Master's degree in Computer Science, Computer Engineering, or a related field, or equivalent practical experience. 7+ years of professional software-engineering experience, with demonstrated impact on large-scale distributed systems or cloud infrastructure. Strong experience designing and operating highly available, scalable, fault-tolerant distributed systems. Proficiency in one or more object-oriented or systems programming languages, such as Java, C++, C#, or Go. Deep understanding of distributed-systems design, data structures, algorithms, operating systems, networking, and secure software-development practices. Experience with system-level test automation, performance/load testing, reliability engineering, and production incident response. Demonstrated experience leading or influencing technical architecture and mentoring engineers. Strong problem-solving, communication, and cross-functional collaboration skills. Preferred Qualifications Experience with Oracle Cloud, AWS, Azure, Google Cloud, or other large-scale cloud platforms. Experience with data-plane platforms, distributed storage, microservices, replication, state management, or high-throughput data processing. Experience defining SLOs, building observability systems, and operating services in a 24x7 production environment. Experience with Infrastructure as Code, service automation, security controls, and compliance requirements for cloud infrastructure. Qualifications Disclaimer: Certain U.S. based or U.S. customer or client-facing roles may be required to comply with applicable requirements, such as immunization/occupational health mandates, and/or drug testing requirements. Range and benefit information provided in this posting are specific to the stated locations only US: Hiring Range in USD from: $114,600 to $234,600 per annum. May be eligible for bonus, equity, and compensation deferral. Oracle maintains broad salary ranges for its roles in order to account for variations in knowledge, skills, experience, market conditions and locations, as well as reflect Oracle's differing products, industries and lines of business. Candidates are typically placed into the range based on the preceding factors as well as internal peer equity. Oracle US offers a comprehensive benefits package which includes the following: 1. Medical, dental, and vision insurance, including expert medical opinion 2. Short term disability and long term disability 3. Life insurance and AD&D 4. Supplemental life insurance (Employee/Spouse/Child) 5. Health care and dependent care Flexible Spending Accounts 6. Pre-tax commuter and parking benefits 7. 401(k) Savings and Investment Plan with company match 8. Paid time off: Flexible Vacation is provided to all eligible employees assigned to a salaried (non-overtime eligible) position. Accrued Vacation is provided to all other employees eligible for vacation benefits. For employees working at least 35 hours per week, the vacation accrual rate is 13 days annually for the first three years of employment and 18 days annually for subsequent years of employment. Vacation accrual is prorated for employees working between 20 and 34 hours per week. Employees working fewer than 20 hours per week are not eligible for vacation. 9. 11 paid holidays 10. Paid sick leave: 72 hours of paid sick leave upon date of hire. Refreshes each calendar year. Unused balance will carry over each year up to a maximum cap of 112 hours. 11. Paid parental leave 12. Adoption assistance 13. Employee Stock Purchase Plan 14. Financial planning and group legal 15. Voluntary benefits including auto, homeowner and pet insurance The role will generally accept applications for at least three calendar days from the posting date or as long as the job remains posted. As part of Oracle's onboarding process and consistent with applicable law, US-based employees are required to complete identity verification, which involves the collection and processing of their biometric information. Accommodations to this requirement may be granted following an individualized assessment. Only Oracle brings together the data, infrastructure, applications, and expertise to power everything from industry innovations to life-saving care. And with AI embedded across our products and services, we help customers turn that promise into a better future for all. Discover your potential at a company leading the way in AI and cloud solutions that impact billions of lives. True innovation starts when everyone is empowered to contribute. That's why we're committed to growing a workforce that promotes opportunities for all with competitive benefits that support our people with flexible medical, life insurance, and retirement options. We also encourage employees to give back to their communities through our volunteer programs. We're committed to including people with disabilities at all stages of the employment process. If you require accessibility assistance or accommodation for a disability at any point, let us know by emailing or by calling 1- in the United States. Oracle is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability and protected veterans' status, or any other characteristic protected by law. Oracle will consider for employment qualified applicants with arrest and conviction records pursuant to applicable law.

At EY, we're all in to shape your future with confidence. We'll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world. The opportunity The Talent Advanced Analytics Lead is responsible for shaping and delivering the organization's next-generation Talent Intelligence and Advanced Analytics strategy. This role combines executive leadership advisory, advanced analytics, AI innovation, talent intelligence, and data product delivery to enable leaders to make faster, more informed decisions to unlock value and drive business impact. The role serves as a strategic advisor to global Talent, Function, Service Line, and Sector leaders by transforming talent, business, operational, and external market data into actionable intelligence. The individual will lead the development of scalable analytics products, AI-powered insights, and agentic solutions that enhance planning, skills intelligence, talent mobility, employee experience, productivity, and organizational effectiveness. Essential Functions: Talent Intelligence Strategy & Executive Advisory Partner with Global Talent Leadership, Function Talent Leaders, Service Line Leaders, and Planning leaders to define and execute the Talent Intelligence strategy. Act as a trusted advisor to executive stakeholders, translating complex workforce trends into strategic recommendations and actionable decisions. Drive data-informed decision making across planning, skills transformation, workforce evolution, talent acquisition, retention, learning, talent mobility, and succession planning, etc. Deliver executive-ready narratives that combine quantitative insights with business context and future workforce implications. Influence enterprise talent priorities through predictive and prescriptive analytics. Advanced Analytics & AI Solutions Lead the development of advanced analytics models to identify workforce risks, forecast talent demand, predict workforce trends, and uncover opportunities to improve organizational performance. Design and deploy AI-powered talent intelligence solutions using machine learning, Generative AI, natural language processing, knowledge graphs, and predictive modelling techniques. Establish scalable approaches for skills intelligence, workforce segmentation, talent forecasting, organizational network analysis, and workforce optimization. Define methodologies that combine internal talent data with external labour market intelligence and economic indicators. Continuously evaluate emerging technologies and analytics techniques to advance talent decision science capabilities. Generative AI, Copilot & Agentic Solutions Lead development of AI-enabled experiences using Data Bricks, Microsoft Fabric, Power BI, Microsoft Copilot, Copilot Studio, Azure AI, enterprise GenAI platforms and machine learning, and intelligent automation capabilities. Design and implement intelligent agents that automate talent insights generation, workforce analytics, executive insights, and decision support processes. Build conversational analytics experiences that enable leaders to interact with talent data through natural language. Establish governance, explainability, responsible AI, and adoption practices for AI-powered talent solutions. Partner with technology teams to integrate agentic workflows into Talent operating models and business processes. Drive experimentation and innovation through AI use cases that unlock measurable business value. Data Products & Platform Leadership Own the vision, roadmap, and lifecycle management of Talent analytics products and self-service insight solutions. Lead development of enterprise Talent data products designed for broad organizational consumption. Establish product management disciplines, user-centric design practices, and adoption strategies across Talent Intelligence initiatives. Drive the transition from static reporting toward intelligent, scalable, reusable analytics products. Identify opportunities to industrialize analytics capabilities and increase insight accessibility across stakeholder groups. Enable scalable analytics architecture supporting structured and unstructured talent data. Collaborate with Data Engineering and Technology teams to optimize data quality, governance, lineage, accessibility, and security. Drive modernization of the talent analytics ecosystem through cloud-native analytics capabilities. Insights, Storytelling & Executive Communications Transform analytical outputs into compelling executive narratives and strategic workforce recommendations. Create executive dashboards and insight products that simplify complex workforce information. Develop thought leadership that shapes future Talent Intelligence capabilities and workforce decision-making practices. Present findings confidently to executive talent leaders and senior business stakeholders. Drive adoption of analytics by making insights easily understandable, relevant, and actionable. Leadership & Capability Development Lead and develop a high-performing team of data scientists, workforce strategists, analytics consultants, AI practitioners, and product managers. Establish talent intelligence standards, methodologies, and governance frameworks. Foster a culture of innovation, experimentation, continuous learning, and responsible AI usage. Build organizational capabilities in analytics, AI literacy, data storytelling, and product thinking. Manage delivery across global, offshore, vendor, and managed-service teams where applicable. Analytical/Decision Making Responsibilities: Determine strategic priorities for Talent Intelligence and Advanced Analytics programs. Prioritize investments and resource allocation across analytics, AI, and data product portfolios. Define and monitor key workforce intelligence metrics and success measures. Evaluate emerging workforce trends, technologies, and market developments to influence strategic direction. Balance innovation investments with operational scalability, governance, and business value realization. Ensure responsible and ethical use of workforce data and AI solutions. Knowledge and Skills Requirements: Strategic & Business Skills Deep understanding of Talent Intelligence, Planning, Talent Analytics, Workforce Evolution and Talent Strategy. Strong consulting, stakeholder management, and executive influence capabilities. Ability to align talent analytics outcomes with broader business objectives. Strong commercial acumen and understanding of organizational transformation. Analytics & Data Science Skills Advanced statistical analysis and predictive modelling, Machine Learning and AI solution design, Experimental design and causal inference methodologies, Skills intelligence and talent marketplace analytics, Expertise in data storytelling and executive reporting. AI & Emerging Technology Skills Generative AI solutions design and implementation, Microsoft Copilot ecosystem expertise, Copilot Studio and conversational AI development, Agentic AI architecture and orchestration, Retrieval-Augmented Generation (RAG) patterns, Prompt engineering and AI governance, Responsible AI and model explainability, Knowledge management and semantic search solutions. Data & Technology Skills Data Bricks, Microsoft Fabric, Power BI and advanced visualization. SQL and advanced data modelling. Microsoft Copilot, Copilot Studio, Azure AI, Enterprise GenAI platforms and Machine Learning Python and R, Modern cloud analytics architectures. API and data integration concepts, Data governance and metadata management. Leadership Competencies Executive presence, Strategic thinking, Innovation mindset, Change leadership. Product-centric thinking, Collaboration across global teams, Enterprise influence and stakeholder engagement. Ability to cope with ambiguity; to drive change and performance outcomes in a complex and agile environment. Supervision Responsibilities: Work closely with the Leads across Global Talent and wider Talent Functions to ensure the provision of services that support business and functional delivery. Lead / manage a team of expert data analytics specialists responsible for functional execution, also build skills and capabilities of the team. Develop AI capabilities, define key AI competencies for the team, and ensure provision of learning to advance skills Independently maintain and leverage (when appropriate) an internal network, including effective partnerships with senior stakeholders, across EY practices / functions that will enable personal effectiveness in the position. Other Requirements: Due to global nature of the role; travel and willingness to work alternative hours will be required. Due to global nature of the role; English language skills - excellent written and verbal communication will be required. Job Requirements: Education: Bachelor's degree in data science, Analytics, Statistics, Computer Science, Economics, Business Analytics, Organizational Psychology, Industrial Engineering, Human Resources, or related discipline. . click apply for full job details

Manages operations for a moderately complex data center, monitoring key metrics, addressing routine issues like capacity and cooling, and recommending improvements aligned with industry best practices. Provides support for escalated technical problems, optimizes automation and monitoring tools, documents processes and incident responses, and contributes to continuous improvement projects. Supports new region builds and expansions, collaborates with project teams, and oversees installations, repairs, inventory, and logistics-leading component upgrades and advising on data center purchases and deployments. Responsibilities Key Responsibilities Data Center Site Portfolio Management: -Typically one data center of moderate complexity. Performance Monitoring and Analysis: -Independently monitors and analyzes data center operations, providing insights and recommendations based on metrics. -Analyzes and resolves routine issues (e.g., physical capacity, power capacity, cooling capacity). -Partners across functions and regions to identify, measure, and improve processes in alignment with industry best practices (e.g., Lean, Six Sigma), contribute to improvement projects, and support alignment with strategic objectives. Issue Management and Automation: -Provides support for escalated complex technical issues. -Triages and/or escalates issues and optimizes the use of automation, scheduling, and monitoring tools to proactively mitigate potential problems. -Identifies, documents, and reviews issues, processes, and solutions, ensuring the data center knowledge base is continually updated. -Executes incident or crisis management protocols in alignment with business continuity plans. -Performs Root Cause Analysis (RCA) following crises or incidents, and updates documentation to capture process improvements. Data Center Expansion Support: -Independently supports new region builds and expansion activities, both onsite and remotely. -Acts as a liaison with project teams and data center engineering, supporting timelines and capacity needs are proactively managed for expansion projects and site builds. -Collaborates closely with project teams on significant aspects of expansion projects and site builds to deliver high standards. Installation and Maintenance: -Oversees installations, repairs, inventory management, and logistics tasks for data centers. -Leads efforts to replace and upgrade components. -Evaluates and recommends purchases or upgrades for data centers. -Plans and oversees rack deployments, installation. Core Responsibilities Planning & Execution: -Independently manages work, monitoring timelines and deliverables to ensure projects or initiatives stay on track and meet requirements. Proactively prioritizes work and adapts to resource or timeline shifts, suggesting adjustments to maintain project efficiency. Collaboration & Partnership: -Collaborates across teams to align on expectations and achieve shared objectives. Builds and maintains a comprehensive understanding of business, stakeholder, and/or customer needs to build and support effective partnerships. Actively listens to diverse perspectives and asks questions to ensure understanding of others. Problem Solving: -Independently identifies and addresses standard and non-standard issues in accordance with standard practices, escalating more complex issues as appropriate. Analyzes data and/or information from multiple sources to troubleshoot standard and non-standard errors. Contributes to knowledge sharing and best practices. Continuous Learning: -Embraces continuous learning by actively seeking to build knowledge and new skills and/or tools and staying current with industry trends and best practices. Seeks out and leverages feedback and training to improve skills. Contributes to a culture of continuous learning and knowledge sharing with team members. Continuous Improvement: -Develops ideas and recommends updates to increase the efficiency and effectiveness of processes, protocols, and workflows within a team. Seeks input from team members on alternative approaches and methods for improving work. Qualifications Disclaimer: Certain U.S. based or U.S. customer or client-facing roles may be required to comply with applicable requirements, such as immunization/occupational health mandates, and/or drug testing requirements. Range and benefit information provided in this posting are specific to the stated locations only US: Hiring Range in USD from: $74,100 to $148,300 per annum. May be eligible for bonus and equity. Oracle maintains broad salary ranges for its roles in order to account for variations in knowledge, skills, experience, market conditions and locations, as well as reflect Oracle's differing products, industries and lines of business. Candidates are typically placed into the range based on the preceding factors as well as internal peer equity. Oracle US offers a comprehensive benefits package which includes the following: 1. Medical, dental, and vision insurance, including expert medical opinion 2. Short term disability and long term disability 3. Life insurance and AD&D 4. Supplemental life insurance (Employee/Spouse/Child) 5. Health care and dependent care Flexible Spending Accounts 6. Pre-tax commuter and parking benefits 7. 401(k) Savings and Investment Plan with company match 8. Paid time off: Flexible Vacation is provided to all eligible employees assigned to a salaried (non-overtime eligible) position. Accrued Vacation is provided to all other employees eligible for vacation benefits. For employees working at least 35 hours per week, the vacation accrual rate is 13 days annually for the first three years of employment and 18 days annually for subsequent years of employment. Vacation accrual is prorated for employees working between 20 and 34 hours per week. Employees working fewer than 20 hours per week are not eligible for vacation. 9. 11 paid holidays 10. Paid sick leave: 72 hours of paid sick leave upon date of hire. Refreshes each calendar year. Unused balance will carry over each year up to a maximum cap of 112 hours. 11. Paid parental leave 12. Adoption assistance 13. Employee Stock Purchase Plan 14. Financial planning and group legal 15. Voluntary benefits including auto, homeowner and pet insurance The role will generally accept applications for at least three calendar days from the posting date or as long as the job remains posted. As part of Oracle's onboarding process and consistent with applicable law, US-based employees are required to complete identity verification, which involves the collection and processing of their biometric information. Accommodations to this requirement may be granted following an individualized assessment. Only Oracle brings together the data, infrastructure, applications, and expertise to power everything from industry innovations to life-saving care. And with AI embedded across our products and services, we help customers turn that promise into a better future for all. Discover your potential at a company leading the way in AI and cloud solutions that impact billions of lives. True innovation starts when everyone is empowered to contribute. That's why we're committed to growing a workforce that promotes opportunities for all with competitive benefits that support our people with flexible medical, life insurance, and retirement options. We also encourage employees to give back to their communities through our volunteer programs. We're committed to including people with disabilities at all stages of the employment process. If you require accessibility assistance or accommodation for a disability at any point, let us know by emailing or by calling 1- in the United States. Oracle is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability and protected veterans' status, or any other characteristic protected by law. Oracle will consider for employment qualified applicants with arrest and conviction records pursuant to applicable law.

Manages team delivering scalable distributed systems and components on a 2-4 quarter horizon. Standardizes engineering practices and scalability requirements across teams; oversees optimization for high throughput, hyper scale workloads; and ensures effective use of distributed state tools and data plane platforms. Guides teams to design fault tolerant, in service upgradable systems, set SLO aligned durability/availability targets, and implement resiliency mechanisms (load shedding, throttling, rate limiting). Provides oversight for KPIs, telemetry, and moderately complex dashboards; directs design of functional/correctness requirements, fault injection tests, and replication/synchronization strategies. Ensures proactive incident management, operational readiness, and on call coverage; drives encryption/access control practices, remediation plans, and compliance documentation. Oversees development and maintenance of automation/IaC and partners with teams on change management plans enabling safe patching, updates, and rollbacks. Responsibilities Key Responsibilities System Design & Architecture - System Scalability: Manages the development and implementation of scalable distributed systems and components across multiple teams, including the effective use of distributed state management tools. Oversees code and/or system optimization efforts for large-scale data processing and high-throughput requirements within and across teams to support hyper-scale systems. Guides teams to define scalability requirements for owned components and ensures design and implementation requirements are met. Manages the use of data plane platforms to effectively handle large-scale data retrieval, storage, and processing. Ensures team accurately designs performance and load testing. System Design & Architecture - System Reliability Design: Manages the strategy for building fault-tolerant components and systems capable of withstanding in-service updates by guiding the implementation of redundancy, replication, and automatic failover mechanisms. Develops design strategies for systems to effectively handle service disruptions (e.g., network partitions) by prioritizing consistency, availability, or partition tolerance. Leads implementation and optimization initiatives across teams for approaches to handle network unreliability, including load-shedding, throttling, and rate-limiting. Guides teams to design components and systems that are durable and adhere to service level objectives (SLOs), setting expectations for availability and durability of other computing services within the department. System Design & Architecture - System Reliability Performance: Provides oversight in defining key performance indicators (KPIs) and telemetry to identify gaps or issues in running systems. Oversees the building and customization of moderately complex dashboards, telemetry systems, and alerting mechanisms to proactively monitor components and system health. System Design & Architecture - Correctness / Availability: Oversees the design and implementation of functional and correctness requirements for feature sets and/or systems in new or existing systems. Guides teams to design complex test scenarios (e.g., fault-injection, brown-out) to evaluate system correctness. Directs implementation strategies for data replication and synchronization techniques to maintain data integrity and availability. Operational Troubleshooting & Incident Management: Guides teams to be proactive when diagnosing, debugging, and resolving issues in active components and systems to support ongoing operation. Ensures teams leverage expertise to prevent interruptions, ensuring no maintenance windows are required for customers and users when resolving issues. Oversees operational readiness protocol and ensures teams remain knowledgeable of owned components and systems to support effective troubleshooting and performance. Oversees and approves schedules for operational support rotations. Compliance & Security: Oversees implementation of robust security measures to protect data and applications in multi-tenant environments, ensuring team strategies incorporate encryption techniques and access controls. Directs execution of remediation plans to address identified security gaps, promoting continuous improvement of security measures. Ensures comprehensive documentation and cloud infrastructure compliance with industry standards and regulations. Automation & Change Management: Oversees the development and maintenance of automation scripts and tools (e.g., Infrastructure as Code (IaC to manage cloud infrastructure. Works with teams to create and adhere to change management plans for patching, updating, and rolling back applications, and guides development of components to allow for automation of these processes. Core Responsibilities Planning & Execution: Manages multiple medium- to large-scale projects or initiatives across teams, ensuring timelines, deliverables, and budgets (when applicable) are monitored and met. Provides direction to teams on project work, setting priorities, and aligning with business needs. Guides teams on adjusting plans to accommodate resource or timeline changes. Collaboration & Partnership: Drives cross-functional partnerships to align on expectations and shared objectives across multiple teams. Coaches team members to develop strategic relationships with business leaders, stakeholders, and external partners to foster collaboration and long-term success. Promotes inclusivity by actively seeking and listening to diverse perspectives, ensuring others feel heard and respected. Problem Solving: Provides direction to multiple teams on addressing complex operational and/or technical issues, as well as guidance on analyzing complex data and/or information to identify solutions. Reviews and provides insights into unresolved or critical issues, helping teams to identify potential solutions. Continuous Learning: Models engaging in continuous learning to deepen expertise and stay ahead of industry trends, integrating best practices into strategic planning. Leverages feedback to drive personal and team skill improvements. Identifies skill gaps across teams and empowers team members to pursue learning and knowledge-sharing opportunities that build their expertise in new areas, coaching them to apply learnings to advance the organization. Continuous Improvement: Drives teams to collaborate on, develop, and implement ideas to increase the efficiency and effectiveness of processes, protocols, and workflows within and across teams, providing oversight. Guides teams to adopt new ideas for alternative approaches and methods and encourages feedback for continued improvement. Performance and Development: Drives performance across teams by providing feedback and coaching in alignment with performance management processes, guidelines, and expectations. Discusses development goals with team members, shares opportunities to facilitate career development, and ensures individual goals are aligned with broader organizational goals. Develops and manages talent acquisition pipeline by leading candidate interviews, monitoring promotion eligibility, and/or orchestrating talent resources. Minimum Job Qualifications Education and/or Experience: •9 years of experience in software development OR •Bachelor's of Technology (B.Tech) Degree in Computer Science, Computer Engineering, Software Engineering, Electrical/Electronics Engineering, Computer Information Systems, Information Systems, Information Technology, Telecommunications, Mathematics, Physics, or related field AND 5 years of experience in software development OR •Bachelor's Degree in Computer Science, Computer Engineering, Software Engineering, Electrical/Electronics Engineering, Computer Information Systems, Information Systems, Information Technology, Telecommunications, Mathematics, Physics, or related field AND 5 years of experience in software development OR •Master's of Technology (M.Tech) Degree in Computer Science, Computer Engineering, Software Engineering, Electrical/Electronics Engineering, Computer Information Systems, Information Systems, Information Technology, Telecommunications, Mathematics, Physics, or related field AND 3 years of experience in software development OR •Master's Degree in Computer Science, Computer Engineering, Software Engineering, Electrical/Electronics Engineering, Computer Information Systems, Information Systems, Information Technology, Telecommunications, Mathematics, Physics, or related field AND 3 years of experience in software development OR •Doctorate in Computer Science, Computer Engineering, Software Engineering, Electrical/Electronics Engineering, Computer Information Systems, Information Systems, Information Technology, Telecommunications, Mathematics, Physics, or related field AND 1 year of experience in software development. Job Skills: Same skills as prior level, plus: •Agile Methodologies: Demonstrated ability to use agile methodologies to drive continuous improvement and product delivery. •Automation: Demonstrated ability in or knowledge of automation, including designing, implementing . click apply for full job details

At EY, we're all in to shape your future with confidence. We'll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world. The opportunity The Talent Advanced Analytics Lead is responsible for shaping and delivering the organization's next-generation Talent Intelligence and Advanced Analytics strategy. This role combines executive leadership advisory, advanced analytics, AI innovation, talent intelligence, and data product delivery to enable leaders to make faster, more informed decisions to unlock value and drive business impact. The role serves as a strategic advisor to global Talent, Function, Service Line, and Sector leaders by transforming talent, business, operational, and external market data into actionable intelligence. The individual will lead the development of scalable analytics products, AI-powered insights, and agentic solutions that enhance planning, skills intelligence, talent mobility, employee experience, productivity, and organizational effectiveness. Essential Functions: Talent Intelligence Strategy & Executive Advisory Partner with Global Talent Leadership, Function Talent Leaders, Service Line Leaders, and Planning leaders to define and execute the Talent Intelligence strategy. Act as a trusted advisor to executive stakeholders, translating complex workforce trends into strategic recommendations and actionable decisions. Drive data-informed decision making across planning, skills transformation, workforce evolution, talent acquisition, retention, learning, talent mobility, and succession planning, etc. Deliver executive-ready narratives that combine quantitative insights with business context and future workforce implications. Influence enterprise talent priorities through predictive and prescriptive analytics. Advanced Analytics & AI Solutions Lead the development of advanced analytics models to identify workforce risks, forecast talent demand, predict workforce trends, and uncover opportunities to improve organizational performance. Design and deploy AI-powered talent intelligence solutions using machine learning, Generative AI, natural language processing, knowledge graphs, and predictive modelling techniques. Establish scalable approaches for skills intelligence, workforce segmentation, talent forecasting, organizational network analysis, and workforce optimization. Define methodologies that combine internal talent data with external labour market intelligence and economic indicators. Continuously evaluate emerging technologies and analytics techniques to advance talent decision science capabilities. Generative AI, Copilot & Agentic Solutions Lead development of AI-enabled experiences using Data Bricks, Microsoft Fabric, Power BI, Microsoft Copilot, Copilot Studio, Azure AI, enterprise GenAI platforms and machine learning, and intelligent automation capabilities. Design and implement intelligent agents that automate talent insights generation, workforce analytics, executive insights, and decision support processes. Build conversational analytics experiences that enable leaders to interact with talent data through natural language. Establish governance, explainability, responsible AI, and adoption practices for AI-powered talent solutions. Partner with technology teams to integrate agentic workflows into Talent operating models and business processes. Drive experimentation and innovation through AI use cases that unlock measurable business value. Data Products & Platform Leadership Own the vision, roadmap, and lifecycle management of Talent analytics products and self-service insight solutions. Lead development of enterprise Talent data products designed for broad organizational consumption. Establish product management disciplines, user-centric design practices, and adoption strategies across Talent Intelligence initiatives. Drive the transition from static reporting toward intelligent, scalable, reusable analytics products. Identify opportunities to industrialize analytics capabilities and increase insight accessibility across stakeholder groups. Enable scalable analytics architecture supporting structured and unstructured talent data. Collaborate with Data Engineering and Technology teams to optimize data quality, governance, lineage, accessibility, and security. Drive modernization of the talent analytics ecosystem through cloud-native analytics capabilities. Insights, Storytelling & Executive Communications Transform analytical outputs into compelling executive narratives and strategic workforce recommendations. Create executive dashboards and insight products that simplify complex workforce information. Develop thought leadership that shapes future Talent Intelligence capabilities and workforce decision-making practices. Present findings confidently to executive talent leaders and senior business stakeholders. Drive adoption of analytics by making insights easily understandable, relevant, and actionable. Leadership & Capability Development Lead and develop a high-performing team of data scientists, workforce strategists, analytics consultants, AI practitioners, and product managers. Establish talent intelligence standards, methodologies, and governance frameworks. Foster a culture of innovation, experimentation, continuous learning, and responsible AI usage. Build organizational capabilities in analytics, AI literacy, data storytelling, and product thinking. Manage delivery across global, offshore, vendor, and managed-service teams where applicable. Analytical/Decision Making Responsibilities: Determine strategic priorities for Talent Intelligence and Advanced Analytics programs. Prioritize investments and resource allocation across analytics, AI, and data product portfolios. Define and monitor key workforce intelligence metrics and success measures. Evaluate emerging workforce trends, technologies, and market developments to influence strategic direction. Balance innovation investments with operational scalability, governance, and business value realization. Ensure responsible and ethical use of workforce data and AI solutions. Knowledge and Skills Requirements: Strategic & Business Skills Deep understanding of Talent Intelligence, Planning, Talent Analytics, Workforce Evolution and Talent Strategy. Strong consulting, stakeholder management, and executive influence capabilities. Ability to align talent analytics outcomes with broader business objectives. Strong commercial acumen and understanding of organizational transformation. Analytics & Data Science Skills Advanced statistical analysis and predictive modelling, Machine Learning and AI solution design, Experimental design and causal inference methodologies, Skills intelligence and talent marketplace analytics, Expertise in data storytelling and executive reporting. AI & Emerging Technology Skills Generative AI solutions design and implementation, Microsoft Copilot ecosystem expertise, Copilot Studio and conversational AI development, Agentic AI architecture and orchestration, Retrieval-Augmented Generation (RAG) patterns, Prompt engineering and AI governance, Responsible AI and model explainability, Knowledge management and semantic search solutions. Data & Technology Skills Data Bricks, Microsoft Fabric, Power BI and advanced visualization. SQL and advanced data modelling. Microsoft Copilot, Copilot Studio, Azure AI, Enterprise GenAI platforms and Machine Learning Python and R, Modern cloud analytics architectures. API and data integration concepts, Data governance and metadata management. Leadership Competencies Executive presence, Strategic thinking, Innovation mindset, Change leadership. Product-centric thinking, Collaboration across global teams, Enterprise influence and stakeholder engagement. Ability to cope with ambiguity; to drive change and performance outcomes in a complex and agile environment. Supervision Responsibilities: Work closely with the Leads across Global Talent and wider Talent Functions to ensure the provision of services that support business and functional delivery. Lead / manage a team of expert data analytics specialists responsible for functional execution, also build skills and capabilities of the team. Develop AI capabilities, define key AI competencies for the team, and ensure provision of learning to advance skills Independently maintain and leverage (when appropriate) an internal network, including effective partnerships with senior stakeholders, across EY practices / functions that will enable personal effectiveness in the position. Other Requirements: Due to global nature of the role; travel and willingness to work alternative hours will be required. Due to global nature of the role; English language skills - excellent written and verbal communication will be required. Job Requirements: Education: Bachelor's degree in data science, Analytics, Statistics, Computer Science, Economics, Business Analytics, Organizational Psychology, Industrial Engineering, Human Resources, or related discipline. . click apply for full job details

At EY, we're all in to shape your future with confidence. We'll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world. The opportunity The Talent Advanced Analytics Lead is responsible for shaping and delivering the organization's next-generation Talent Intelligence and Advanced Analytics strategy. This role combines executive leadership advisory, advanced analytics, AI innovation, talent intelligence, and data product delivery to enable leaders to make faster, more informed decisions to unlock value and drive business impact. The role serves as a strategic advisor to global Talent, Function, Service Line, and Sector leaders by transforming talent, business, operational, and external market data into actionable intelligence. The individual will lead the development of scalable analytics products, AI-powered insights, and agentic solutions that enhance planning, skills intelligence, talent mobility, employee experience, productivity, and organizational effectiveness. Essential Functions: Talent Intelligence Strategy & Executive Advisory Partner with Global Talent Leadership, Function Talent Leaders, Service Line Leaders, and Planning leaders to define and execute the Talent Intelligence strategy. Act as a trusted advisor to executive stakeholders, translating complex workforce trends into strategic recommendations and actionable decisions. Drive data-informed decision making across planning, skills transformation, workforce evolution, talent acquisition, retention, learning, talent mobility, and succession planning, etc. Deliver executive-ready narratives that combine quantitative insights with business context and future workforce implications. Influence enterprise talent priorities through predictive and prescriptive analytics. Advanced Analytics & AI Solutions Lead the development of advanced analytics models to identify workforce risks, forecast talent demand, predict workforce trends, and uncover opportunities to improve organizational performance. Design and deploy AI-powered talent intelligence solutions using machine learning, Generative AI, natural language processing, knowledge graphs, and predictive modelling techniques. Establish scalable approaches for skills intelligence, workforce segmentation, talent forecasting, organizational network analysis, and workforce optimization. Define methodologies that combine internal talent data with external labour market intelligence and economic indicators. Continuously evaluate emerging technologies and analytics techniques to advance talent decision science capabilities. Generative AI, Copilot & Agentic Solutions Lead development of AI-enabled experiences using Data Bricks, Microsoft Fabric, Power BI, Microsoft Copilot, Copilot Studio, Azure AI, enterprise GenAI platforms and machine learning, and intelligent automation capabilities. Design and implement intelligent agents that automate talent insights generation, workforce analytics, executive insights, and decision support processes. Build conversational analytics experiences that enable leaders to interact with talent data through natural language. Establish governance, explainability, responsible AI, and adoption practices for AI-powered talent solutions. Partner with technology teams to integrate agentic workflows into Talent operating models and business processes. Drive experimentation and innovation through AI use cases that unlock measurable business value. Data Products & Platform Leadership Own the vision, roadmap, and lifecycle management of Talent analytics products and self-service insight solutions. Lead development of enterprise Talent data products designed for broad organizational consumption. Establish product management disciplines, user-centric design practices, and adoption strategies across Talent Intelligence initiatives. Drive the transition from static reporting toward intelligent, scalable, reusable analytics products. Identify opportunities to industrialize analytics capabilities and increase insight accessibility across stakeholder groups. Enable scalable analytics architecture supporting structured and unstructured talent data. Collaborate with Data Engineering and Technology teams to optimize data quality, governance, lineage, accessibility, and security. Drive modernization of the talent analytics ecosystem through cloud-native analytics capabilities. Insights, Storytelling & Executive Communications Transform analytical outputs into compelling executive narratives and strategic workforce recommendations. Create executive dashboards and insight products that simplify complex workforce information. Develop thought leadership that shapes future Talent Intelligence capabilities and workforce decision-making practices. Present findings confidently to executive talent leaders and senior business stakeholders. Drive adoption of analytics by making insights easily understandable, relevant, and actionable. Leadership & Capability Development Lead and develop a high-performing team of data scientists, workforce strategists, analytics consultants, AI practitioners, and product managers. Establish talent intelligence standards, methodologies, and governance frameworks. Foster a culture of innovation, experimentation, continuous learning, and responsible AI usage. Build organizational capabilities in analytics, AI literacy, data storytelling, and product thinking. Manage delivery across global, offshore, vendor, and managed-service teams where applicable. Analytical/Decision Making Responsibilities: Determine strategic priorities for Talent Intelligence and Advanced Analytics programs. Prioritize investments and resource allocation across analytics, AI, and data product portfolios. Define and monitor key workforce intelligence metrics and success measures. Evaluate emerging workforce trends, technologies, and market developments to influence strategic direction. Balance innovation investments with operational scalability, governance, and business value realization. Ensure responsible and ethical use of workforce data and AI solutions. Knowledge and Skills Requirements: Strategic & Business Skills Deep understanding of Talent Intelligence, Planning, Talent Analytics, Workforce Evolution and Talent Strategy. Strong consulting, stakeholder management, and executive influence capabilities. Ability to align talent analytics outcomes with broader business objectives. Strong commercial acumen and understanding of organizational transformation. Analytics & Data Science Skills Advanced statistical analysis and predictive modelling, Machine Learning and AI solution design, Experimental design and causal inference methodologies, Skills intelligence and talent marketplace analytics, Expertise in data storytelling and executive reporting. AI & Emerging Technology Skills Generative AI solutions design and implementation, Microsoft Copilot ecosystem expertise, Copilot Studio and conversational AI development, Agentic AI architecture and orchestration, Retrieval-Augmented Generation (RAG) patterns, Prompt engineering and AI governance, Responsible AI and model explainability, Knowledge management and semantic search solutions. Data & Technology Skills Data Bricks, Microsoft Fabric, Power BI and advanced visualization. SQL and advanced data modelling. Microsoft Copilot, Copilot Studio, Azure AI, Enterprise GenAI platforms and Machine Learning Python and R, Modern cloud analytics architectures. API and data integration concepts, Data governance and metadata management. Leadership Competencies Executive presence, Strategic thinking, Innovation mindset, Change leadership. Product-centric thinking, Collaboration across global teams, Enterprise influence and stakeholder engagement. Ability to cope with ambiguity; to drive change and performance outcomes in a complex and agile environment. Supervision Responsibilities: Work closely with the Leads across Global Talent and wider Talent Functions to ensure the provision of services that support business and functional delivery. Lead / manage a team of expert data analytics specialists responsible for functional execution, also build skills and capabilities of the team. Develop AI capabilities, define key AI competencies for the team, and ensure provision of learning to advance skills Independently maintain and leverage (when appropriate) an internal network, including effective partnerships with senior stakeholders, across EY practices / functions that will enable personal effectiveness in the position. Other Requirements: Due to global nature of the role; travel and willingness to work alternative hours will be required. Due to global nature of the role; English language skills - excellent written and verbal communication will be required. Job Requirements: Education: Bachelor's degree in data science, Analytics, Statistics, Computer Science, Economics, Business Analytics, Organizational Psychology, Industrial Engineering, Human Resources, or related discipline. . click apply for full job details

At EY, we're all in to shape your future with confidence. We'll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world. The opportunity The Talent Advanced Analytics Lead is responsible for shaping and delivering the organization's next-generation Talent Intelligence and Advanced Analytics strategy. This role combines executive leadership advisory, advanced analytics, AI innovation, talent intelligence, and data product delivery to enable leaders to make faster, more informed decisions to unlock value and drive business impact. The role serves as a strategic advisor to global Talent, Function, Service Line, and Sector leaders by transforming talent, business, operational, and external market data into actionable intelligence. The individual will lead the development of scalable analytics products, AI-powered insights, and agentic solutions that enhance planning, skills intelligence, talent mobility, employee experience, productivity, and organizational effectiveness. Essential Functions: Talent Intelligence Strategy & Executive Advisory Partner with Global Talent Leadership, Function Talent Leaders, Service Line Leaders, and Planning leaders to define and execute the Talent Intelligence strategy. Act as a trusted advisor to executive stakeholders, translating complex workforce trends into strategic recommendations and actionable decisions. Drive data-informed decision making across planning, skills transformation, workforce evolution, talent acquisition, retention, learning, talent mobility, and succession planning, etc. Deliver executive-ready narratives that combine quantitative insights with business context and future workforce implications. Influence enterprise talent priorities through predictive and prescriptive analytics. Advanced Analytics & AI Solutions Lead the development of advanced analytics models to identify workforce risks, forecast talent demand, predict workforce trends, and uncover opportunities to improve organizational performance. Design and deploy AI-powered talent intelligence solutions using machine learning, Generative AI, natural language processing, knowledge graphs, and predictive modelling techniques. Establish scalable approaches for skills intelligence, workforce segmentation, talent forecasting, organizational network analysis, and workforce optimization. Define methodologies that combine internal talent data with external labour market intelligence and economic indicators. Continuously evaluate emerging technologies and analytics techniques to advance talent decision science capabilities. Generative AI, Copilot & Agentic Solutions Lead development of AI-enabled experiences using Data Bricks, Microsoft Fabric, Power BI, Microsoft Copilot, Copilot Studio, Azure AI, enterprise GenAI platforms and machine learning, and intelligent automation capabilities. Design and implement intelligent agents that automate talent insights generation, workforce analytics, executive insights, and decision support processes. Build conversational analytics experiences that enable leaders to interact with talent data through natural language. Establish governance, explainability, responsible AI, and adoption practices for AI-powered talent solutions. Partner with technology teams to integrate agentic workflows into Talent operating models and business processes. Drive experimentation and innovation through AI use cases that unlock measurable business value. Data Products & Platform Leadership Own the vision, roadmap, and lifecycle management of Talent analytics products and self-service insight solutions. Lead development of enterprise Talent data products designed for broad organizational consumption. Establish product management disciplines, user-centric design practices, and adoption strategies across Talent Intelligence initiatives. Drive the transition from static reporting toward intelligent, scalable, reusable analytics products. Identify opportunities to industrialize analytics capabilities and increase insight accessibility across stakeholder groups. Enable scalable analytics architecture supporting structured and unstructured talent data. Collaborate with Data Engineering and Technology teams to optimize data quality, governance, lineage, accessibility, and security. Drive modernization of the talent analytics ecosystem through cloud-native analytics capabilities. Insights, Storytelling & Executive Communications Transform analytical outputs into compelling executive narratives and strategic workforce recommendations. Create executive dashboards and insight products that simplify complex workforce information. Develop thought leadership that shapes future Talent Intelligence capabilities and workforce decision-making practices. Present findings confidently to executive talent leaders and senior business stakeholders. Drive adoption of analytics by making insights easily understandable, relevant, and actionable. Leadership & Capability Development Lead and develop a high-performing team of data scientists, workforce strategists, analytics consultants, AI practitioners, and product managers. Establish talent intelligence standards, methodologies, and governance frameworks. Foster a culture of innovation, experimentation, continuous learning, and responsible AI usage. Build organizational capabilities in analytics, AI literacy, data storytelling, and product thinking. Manage delivery across global, offshore, vendor, and managed-service teams where applicable. Analytical/Decision Making Responsibilities: Determine strategic priorities for Talent Intelligence and Advanced Analytics programs. Prioritize investments and resource allocation across analytics, AI, and data product portfolios. Define and monitor key workforce intelligence metrics and success measures. Evaluate emerging workforce trends, technologies, and market developments to influence strategic direction. Balance innovation investments with operational scalability, governance, and business value realization. Ensure responsible and ethical use of workforce data and AI solutions. Knowledge and Skills Requirements: Strategic & Business Skills Deep understanding of Talent Intelligence, Planning, Talent Analytics, Workforce Evolution and Talent Strategy. Strong consulting, stakeholder management, and executive influence capabilities. Ability to align talent analytics outcomes with broader business objectives. Strong commercial acumen and understanding of organizational transformation. Analytics & Data Science Skills Advanced statistical analysis and predictive modelling, Machine Learning and AI solution design, Experimental design and causal inference methodologies, Skills intelligence and talent marketplace analytics, Expertise in data storytelling and executive reporting. AI & Emerging Technology Skills Generative AI solutions design and implementation, Microsoft Copilot ecosystem expertise, Copilot Studio and conversational AI development, Agentic AI architecture and orchestration, Retrieval-Augmented Generation (RAG) patterns, Prompt engineering and AI governance, Responsible AI and model explainability, Knowledge management and semantic search solutions. Data & Technology Skills Data Bricks, Microsoft Fabric, Power BI and advanced visualization. SQL and advanced data modelling. Microsoft Copilot, Copilot Studio, Azure AI, Enterprise GenAI platforms and Machine Learning Python and R, Modern cloud analytics architectures. API and data integration concepts, Data governance and metadata management. Leadership Competencies Executive presence, Strategic thinking, Innovation mindset, Change leadership. Product-centric thinking, Collaboration across global teams, Enterprise influence and stakeholder engagement. Ability to cope with ambiguity; to drive change and performance outcomes in a complex and agile environment. Supervision Responsibilities: Work closely with the Leads across Global Talent and wider Talent Functions to ensure the provision of services that support business and functional delivery. Lead / manage a team of expert data analytics specialists responsible for functional execution, also build skills and capabilities of the team. Develop AI capabilities, define key AI competencies for the team, and ensure provision of learning to advance skills Independently maintain and leverage (when appropriate) an internal network, including effective partnerships with senior stakeholders, across EY practices / functions that will enable personal effectiveness in the position. Other Requirements: Due to global nature of the role; travel and willingness to work alternative hours will be required. Due to global nature of the role; English language skills - excellent written and verbal communication will be required. Job Requirements: Education: Bachelor's degree in data science, Analytics, Statistics, Computer Science, Economics, Business Analytics, Organizational Psychology, Industrial Engineering, Human Resources, or related discipline. . click apply for full job details

At EY, we're all in to shape your future with confidence. We'll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world. The opportunity The Talent Advanced Analytics Lead is responsible for shaping and delivering the organization's next-generation Talent Intelligence and Advanced Analytics strategy. This role combines executive leadership advisory, advanced analytics, AI innovation, talent intelligence, and data product delivery to enable leaders to make faster, more informed decisions to unlock value and drive business impact. The role serves as a strategic advisor to global Talent, Function, Service Line, and Sector leaders by transforming talent, business, operational, and external market data into actionable intelligence. The individual will lead the development of scalable analytics products, AI-powered insights, and agentic solutions that enhance planning, skills intelligence, talent mobility, employee experience, productivity, and organizational effectiveness. Essential Functions: Talent Intelligence Strategy & Executive Advisory Partner with Global Talent Leadership, Function Talent Leaders, Service Line Leaders, and Planning leaders to define and execute the Talent Intelligence strategy. Act as a trusted advisor to executive stakeholders, translating complex workforce trends into strategic recommendations and actionable decisions. Drive data-informed decision making across planning, skills transformation, workforce evolution, talent acquisition, retention, learning, talent mobility, and succession planning, etc. Deliver executive-ready narratives that combine quantitative insights with business context and future workforce implications. Influence enterprise talent priorities through predictive and prescriptive analytics. Advanced Analytics & AI Solutions Lead the development of advanced analytics models to identify workforce risks, forecast talent demand, predict workforce trends, and uncover opportunities to improve organizational performance. Design and deploy AI-powered talent intelligence solutions using machine learning, Generative AI, natural language processing, knowledge graphs, and predictive modelling techniques. Establish scalable approaches for skills intelligence, workforce segmentation, talent forecasting, organizational network analysis, and workforce optimization. Define methodologies that combine internal talent data with external labour market intelligence and economic indicators. Continuously evaluate emerging technologies and analytics techniques to advance talent decision science capabilities. Generative AI, Copilot & Agentic Solutions Lead development of AI-enabled experiences using Data Bricks, Microsoft Fabric, Power BI, Microsoft Copilot, Copilot Studio, Azure AI, enterprise GenAI platforms and machine learning, and intelligent automation capabilities. Design and implement intelligent agents that automate talent insights generation, workforce analytics, executive insights, and decision support processes. Build conversational analytics experiences that enable leaders to interact with talent data through natural language. Establish governance, explainability, responsible AI, and adoption practices for AI-powered talent solutions. Partner with technology teams to integrate agentic workflows into Talent operating models and business processes. Drive experimentation and innovation through AI use cases that unlock measurable business value. Data Products & Platform Leadership Own the vision, roadmap, and lifecycle management of Talent analytics products and self-service insight solutions. Lead development of enterprise Talent data products designed for broad organizational consumption. Establish product management disciplines, user-centric design practices, and adoption strategies across Talent Intelligence initiatives. Drive the transition from static reporting toward intelligent, scalable, reusable analytics products. Identify opportunities to industrialize analytics capabilities and increase insight accessibility across stakeholder groups. Enable scalable analytics architecture supporting structured and unstructured talent data. Collaborate with Data Engineering and Technology teams to optimize data quality, governance, lineage, accessibility, and security. Drive modernization of the talent analytics ecosystem through cloud-native analytics capabilities. Insights, Storytelling & Executive Communications Transform analytical outputs into compelling executive narratives and strategic workforce recommendations. Create executive dashboards and insight products that simplify complex workforce information. Develop thought leadership that shapes future Talent Intelligence capabilities and workforce decision-making practices. Present findings confidently to executive talent leaders and senior business stakeholders. Drive adoption of analytics by making insights easily understandable, relevant, and actionable. Leadership & Capability Development Lead and develop a high-performing team of data scientists, workforce strategists, analytics consultants, AI practitioners, and product managers. Establish talent intelligence standards, methodologies, and governance frameworks. Foster a culture of innovation, experimentation, continuous learning, and responsible AI usage. Build organizational capabilities in analytics, AI literacy, data storytelling, and product thinking. Manage delivery across global, offshore, vendor, and managed-service teams where applicable. Analytical/Decision Making Responsibilities: Determine strategic priorities for Talent Intelligence and Advanced Analytics programs. Prioritize investments and resource allocation across analytics, AI, and data product portfolios. Define and monitor key workforce intelligence metrics and success measures. Evaluate emerging workforce trends, technologies, and market developments to influence strategic direction. Balance innovation investments with operational scalability, governance, and business value realization. Ensure responsible and ethical use of workforce data and AI solutions. Knowledge and Skills Requirements: Strategic & Business Skills Deep understanding of Talent Intelligence, Planning, Talent Analytics, Workforce Evolution and Talent Strategy. Strong consulting, stakeholder management, and executive influence capabilities. Ability to align talent analytics outcomes with broader business objectives. Strong commercial acumen and understanding of organizational transformation. Analytics & Data Science Skills Advanced statistical analysis and predictive modelling, Machine Learning and AI solution design, Experimental design and causal inference methodologies, Skills intelligence and talent marketplace analytics, Expertise in data storytelling and executive reporting. AI & Emerging Technology Skills Generative AI solutions design and implementation, Microsoft Copilot ecosystem expertise, Copilot Studio and conversational AI development, Agentic AI architecture and orchestration, Retrieval-Augmented Generation (RAG) patterns, Prompt engineering and AI governance, Responsible AI and model explainability, Knowledge management and semantic search solutions. Data & Technology Skills Data Bricks, Microsoft Fabric, Power BI and advanced visualization. SQL and advanced data modelling. Microsoft Copilot, Copilot Studio, Azure AI, Enterprise GenAI platforms and Machine Learning Python and R, Modern cloud analytics architectures. API and data integration concepts, Data governance and metadata management. Leadership Competencies Executive presence, Strategic thinking, Innovation mindset, Change leadership. Product-centric thinking, Collaboration across global teams, Enterprise influence and stakeholder engagement. Ability to cope with ambiguity; to drive change and performance outcomes in a complex and agile environment. Supervision Responsibilities: Work closely with the Leads across Global Talent and wider Talent Functions to ensure the provision of services that support business and functional delivery. Lead / manage a team of expert data analytics specialists responsible for functional execution, also build skills and capabilities of the team. Develop AI capabilities, define key AI competencies for the team, and ensure provision of learning to advance skills Independently maintain and leverage (when appropriate) an internal network, including effective partnerships with senior stakeholders, across EY practices / functions that will enable personal effectiveness in the position. Other Requirements: Due to global nature of the role; travel and willingness to work alternative hours will be required. Due to global nature of the role; English language skills - excellent written and verbal communication will be required. Job Requirements: Education: Bachelor's degree in data science, Analytics, Statistics, Computer Science, Economics, Business Analytics, Organizational Psychology, Industrial Engineering, Human Resources, or related discipline. . click apply for full job details

At EY, we're all in to shape your future with confidence. We'll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world. The opportunity The Talent Advanced Analytics Lead is responsible for shaping and delivering the organization's next-generation Talent Intelligence and Advanced Analytics strategy. This role combines executive leadership advisory, advanced analytics, AI innovation, talent intelligence, and data product delivery to enable leaders to make faster, more informed decisions to unlock value and drive business impact. The role serves as a strategic advisor to global Talent, Function, Service Line, and Sector leaders by transforming talent, business, operational, and external market data into actionable intelligence. The individual will lead the development of scalable analytics products, AI-powered insights, and agentic solutions that enhance planning, skills intelligence, talent mobility, employee experience, productivity, and organizational effectiveness. Essential Functions: Talent Intelligence Strategy & Executive Advisory Partner with Global Talent Leadership, Function Talent Leaders, Service Line Leaders, and Planning leaders to define and execute the Talent Intelligence strategy. Act as a trusted advisor to executive stakeholders, translating complex workforce trends into strategic recommendations and actionable decisions. Drive data-informed decision making across planning, skills transformation, workforce evolution, talent acquisition, retention, learning, talent mobility, and succession planning, etc. Deliver executive-ready narratives that combine quantitative insights with business context and future workforce implications. Influence enterprise talent priorities through predictive and prescriptive analytics. Advanced Analytics & AI Solutions Lead the development of advanced analytics models to identify workforce risks, forecast talent demand, predict workforce trends, and uncover opportunities to improve organizational performance. Design and deploy AI-powered talent intelligence solutions using machine learning, Generative AI, natural language processing, knowledge graphs, and predictive modelling techniques. Establish scalable approaches for skills intelligence, workforce segmentation, talent forecasting, organizational network analysis, and workforce optimization. Define methodologies that combine internal talent data with external labour market intelligence and economic indicators. Continuously evaluate emerging technologies and analytics techniques to advance talent decision science capabilities. Generative AI, Copilot & Agentic Solutions Lead development of AI-enabled experiences using Data Bricks, Microsoft Fabric, Power BI, Microsoft Copilot, Copilot Studio, Azure AI, enterprise GenAI platforms and machine learning, and intelligent automation capabilities. Design and implement intelligent agents that automate talent insights generation, workforce analytics, executive insights, and decision support processes. Build conversational analytics experiences that enable leaders to interact with talent data through natural language. Establish governance, explainability, responsible AI, and adoption practices for AI-powered talent solutions. Partner with technology teams to integrate agentic workflows into Talent operating models and business processes. Drive experimentation and innovation through AI use cases that unlock measurable business value. Data Products & Platform Leadership Own the vision, roadmap, and lifecycle management of Talent analytics products and self-service insight solutions. Lead development of enterprise Talent data products designed for broad organizational consumption. Establish product management disciplines, user-centric design practices, and adoption strategies across Talent Intelligence initiatives. Drive the transition from static reporting toward intelligent, scalable, reusable analytics products. Identify opportunities to industrialize analytics capabilities and increase insight accessibility across stakeholder groups. Enable scalable analytics architecture supporting structured and unstructured talent data. Collaborate with Data Engineering and Technology teams to optimize data quality, governance, lineage, accessibility, and security. Drive modernization of the talent analytics ecosystem through cloud-native analytics capabilities. Insights, Storytelling & Executive Communications Transform analytical outputs into compelling executive narratives and strategic workforce recommendations. Create executive dashboards and insight products that simplify complex workforce information. Develop thought leadership that shapes future Talent Intelligence capabilities and workforce decision-making practices. Present findings confidently to executive talent leaders and senior business stakeholders. Drive adoption of analytics by making insights easily understandable, relevant, and actionable. Leadership & Capability Development Lead and develop a high-performing team of data scientists, workforce strategists, analytics consultants, AI practitioners, and product managers. Establish talent intelligence standards, methodologies, and governance frameworks. Foster a culture of innovation, experimentation, continuous learning, and responsible AI usage. Build organizational capabilities in analytics, AI literacy, data storytelling, and product thinking. Manage delivery across global, offshore, vendor, and managed-service teams where applicable. Analytical/Decision Making Responsibilities: Determine strategic priorities for Talent Intelligence and Advanced Analytics programs. Prioritize investments and resource allocation across analytics, AI, and data product portfolios. Define and monitor key workforce intelligence metrics and success measures. Evaluate emerging workforce trends, technologies, and market developments to influence strategic direction. Balance innovation investments with operational scalability, governance, and business value realization. Ensure responsible and ethical use of workforce data and AI solutions. Knowledge and Skills Requirements: Strategic & Business Skills Deep understanding of Talent Intelligence, Planning, Talent Analytics, Workforce Evolution and Talent Strategy. Strong consulting, stakeholder management, and executive influence capabilities. Ability to align talent analytics outcomes with broader business objectives. Strong commercial acumen and understanding of organizational transformation. Analytics & Data Science Skills Advanced statistical analysis and predictive modelling, Machine Learning and AI solution design, Experimental design and causal inference methodologies, Skills intelligence and talent marketplace analytics, Expertise in data storytelling and executive reporting. AI & Emerging Technology Skills Generative AI solutions design and implementation, Microsoft Copilot ecosystem expertise, Copilot Studio and conversational AI development, Agentic AI architecture and orchestration, Retrieval-Augmented Generation (RAG) patterns, Prompt engineering and AI governance, Responsible AI and model explainability, Knowledge management and semantic search solutions. Data & Technology Skills Data Bricks, Microsoft Fabric, Power BI and advanced visualization. SQL and advanced data modelling. Microsoft Copilot, Copilot Studio, Azure AI, Enterprise GenAI platforms and Machine Learning Python and R, Modern cloud analytics architectures. API and data integration concepts, Data governance and metadata management. Leadership Competencies Executive presence, Strategic thinking, Innovation mindset, Change leadership. Product-centric thinking, Collaboration across global teams, Enterprise influence and stakeholder engagement. Ability to cope with ambiguity; to drive change and performance outcomes in a complex and agile environment. Supervision Responsibilities: Work closely with the Leads across Global Talent and wider Talent Functions to ensure the provision of services that support business and functional delivery. Lead / manage a team of expert data analytics specialists responsible for functional execution, also build skills and capabilities of the team. Develop AI capabilities, define key AI competencies for the team, and ensure provision of learning to advance skills Independently maintain and leverage (when appropriate) an internal network, including effective partnerships with senior stakeholders, across EY practices / functions that will enable personal effectiveness in the position. Other Requirements: Due to global nature of the role; travel and willingness to work alternative hours will be required. Due to global nature of the role; English language skills - excellent written and verbal communication will be required. Job Requirements: Education: Bachelor's degree in data science, Analytics, Statistics, Computer Science, Economics, Business Analytics, Organizational Psychology, Industrial Engineering, Human Resources, or related discipline. . click apply for full job details