Takeda Pharmaceutical
Cambridge, Massachusetts
By clicking the "Apply" button, I understand that my employment application process with Takeda will commence and that the information I provide in my application will be processed in line with Takeda's Privacy Notice and Terms of Use. I further attest that all information I submit in my employment application is true to the best of my knowledge. Find out if this opportunity is a good fit by reading all of the information that follows below. Job Description Director, Computational & AI Biologics Design Lead Takeda Research is constructing a Lab of Tomorrow built on AI, automation, new ways of working, and talent with the singular vision of delivering differentiated medicines to the clinic at speed and cost. To catalyze these efforts, Takeda is creating two complementary units: AI Research Accelerator (AIRx) and Discovery Automation & Robotics (DAR). AIRx will have a group of a dedicated group of experienced biologic drug hunters with the autonomy of a biotech and the resources of a leading pharmaceutical company. It is designed to incubate the future AI-powered operating models for large molecule discovery and deliver candidates to the clinic at industry leading speed and success rates. Purpose Reporting to the Head of AIRx, the Computational & AI Biologics Design Lead sits at the scientific heart of the Takeda Boston (TBOS) Large Molecule Pod. As part of the AIRx team, this role serves as a strategic computational leader, driving in silico biologics design and shaping how AI-enabled biologics discovery is executed for select programs. This role drives in silico biologics design, applies generative AI and structure-informed methods to antibody and large-molecule programs, and connects Takeda's internal AI/ML platform capabilities to the day-to-day decisions of a fast-moving drug-hunting team. In addition, the role defines decision frameworks and scientific standards that influence candidate prioritization, progression, and overall portfolio direction. Proposals from this role directly shape what gets engineered, what gets deprioritized, and what ultimately reaches the clinic. The role is deeply hands-on, with a mandate to operate with urgency and independence while remaining tightly integrated with biology, protein engineering, and translational science colleagues across the pod. Key Accountabilities 1. In Silico Biologics Design for Pod Programs Define and drive the computational design strategy across the pod's large-molecule programs, including antibody, VHH, and multispecific or fusion formats, from early format selection through lead optimization. Design and prioritize molecular candidates using generative AI/ML and computational modeling approaches Serve as a scientific advisor to pod leadership on computational design decisions, influencing program direction and key trade-offs Partner closely with the Biologics Discovery Lead to translate computational proposals into testable engineering priorities; challenge and be challenged on scientific assumptions in equal measure. Integrate structural biology data into design strategies to inform format selection, epitope targeting, and interface optimization. Oversee virtual screening, binding affinity prediction, and developability risk assessment for candidate sequences; provide ranked shortlists with quantified uncertainty to the pod. Establish and improve approaches to accelerate lead optimization by compressing DMTA cycles through AI-guided design, with the goal of achieving the target candidate profile in fewer rounds. Collaborate with translational and DMPK scientists to model PK/PD behavior, TMDD, and species cross-reactivity in silico, informing study design and reducing in vivo cycle time. 2. AI/ML Platform Interface and Data Strategy Serve as the pod's primary computational interface to Takeda's AI/ML research platform; evaluate and benchmark new AI design tools against the pod's specific biologics modalities and program needs. Define and steward data requirements for AI model training within the pod: structure data return from experimental campaigns, annotation standards, and integration with Takeda's data infrastructure. Contribute to building and curating AI/ML training datasets from pod experimental outputs to enable continuous model improvement. Guide development and refinement of computational workflows to enable pod scalability, speed and reproducibility across the DMTA cycle; document methods to support cross-pod learning. 3. Pod Integration and Scientific Operations Act as a hands-on computational authority within pod governance: prepare and present in silico analyses for PRC reviews, design review boards, and candidate declaration milestones. Ensure computational requirements are integrated early in external experimental campaigns to maximize data return value. Interface with Takeda's discovery automation capabilities to define assay and data readout specifications for pod programs entering automated workflows when applicable. 4. Scientific Leadership and External Engagement Maintain deep subject-matter expertise by staying current with advances in AI for biologics design and structure prediction; translate emerging capabilities into actionable proposals for the pod. Identify and translate relevant external innovations into opportunities that enhance pod capabilities and programs Represent Takeda's computational biologics capabilities in interactions with external partners, at conferences, and in the scientific community; contribute to publications and IP filings as appropriate. Provide scientific mentorship within the AIRx context and help shape computational biologics practices across the broader research organization. Qualifications & Competencies Expected Requirements: PhD in Computational Biology, Bioinformatics, Structural Biology, Computer Science, or a closely related discipline. 10+ years of drug discovery experience with a demonstrated track record of computational impact on large-molecule or biologics programs; industry experience strongly preferred. Deep expertise in antibody and protein sequence, structure, and function modeling, with proficiency in generative or predictive AI frameworks applied to biologics design. Broad proficiency in computational tools relevant to biologics, spanning structural analysis, molecular simulation, developability prediction, and bioinformatics. Strong coding skills (Python required); experience building and deploying ML models in a drug discovery context; familiarity with cloud-based compute and MLOps practices. Demonstrated ability to operate as both a technical individual contributor and a cross-functional scientific partner in a fast-paced, program-driven environment. Versatile communicator: able to present complex computational findings to biologists, clinical scientists, and senior leadership with clarity and scientific rigor. Preferred Experience with multispecific antibody formats and the associated engineering, developability, and PK/PD considerations. Experience integrating physics-based modeling with deep learning approaches to improve prediction accuracy and generalization. Prior experience defining data requirements and governance for AI/ML platform development across multiple programs or sites. Experience operating within or alongside an external AI design partner environment, including co-design workflows and campaign-level data return. Track record of contributing to IND-enabling programs; familiarity with candidate declaration criteria and biologics CMC considerations. ADDITIONAL INFORMATION The position will be based in Cambridge, MA. This position is currently classified as "hybrid" by Takeda's Hybrid and Remote Work policy Takeda Compensation and Benefits Summary We understand compensation is an important factor as you consider the next step in your career. We are committed to equitable pay for all employees, and we strive to be more transparent with our pay practices. For Location: Boston, MA U.S. Base Salary Range: $177,000.00 - $278,080.00 The estimated salary range reflects an anticipated range for this position. The actual base salary offered may depend on a variety of factors, including the qualifications of the individual applicant for the position, years of relevant experience, specific and unique skills, level of education attained, certifications or other professional licenses held, and the location in which the applicant lives and/or from which they will be performing the job. The actual base salary offered will be in accordance with state or local minimum wage requirements for the job location. U. xibtplm S. based employees may be eligible for short-term and/ or long-term incentives. U.S. based employees may be eligible to participate in medical, dental, vision insurance, a 401(k) plan and
By clicking the "Apply" button, I understand that my employment application process with Takeda will commence and that the information I provide in my application will be processed in line with Takeda's Privacy Notice and Terms of Use. I further attest that all information I submit in my employment application is true to the best of my knowledge. Find out if this opportunity is a good fit by reading all of the information that follows below. Job Description Director, Computational & AI Biologics Design Lead Takeda Research is constructing a Lab of Tomorrow built on AI, automation, new ways of working, and talent with the singular vision of delivering differentiated medicines to the clinic at speed and cost. To catalyze these efforts, Takeda is creating two complementary units: AI Research Accelerator (AIRx) and Discovery Automation & Robotics (DAR). AIRx will have a group of a dedicated group of experienced biologic drug hunters with the autonomy of a biotech and the resources of a leading pharmaceutical company. It is designed to incubate the future AI-powered operating models for large molecule discovery and deliver candidates to the clinic at industry leading speed and success rates. Purpose Reporting to the Head of AIRx, the Computational & AI Biologics Design Lead sits at the scientific heart of the Takeda Boston (TBOS) Large Molecule Pod. As part of the AIRx team, this role serves as a strategic computational leader, driving in silico biologics design and shaping how AI-enabled biologics discovery is executed for select programs. This role drives in silico biologics design, applies generative AI and structure-informed methods to antibody and large-molecule programs, and connects Takeda's internal AI/ML platform capabilities to the day-to-day decisions of a fast-moving drug-hunting team. In addition, the role defines decision frameworks and scientific standards that influence candidate prioritization, progression, and overall portfolio direction. Proposals from this role directly shape what gets engineered, what gets deprioritized, and what ultimately reaches the clinic. The role is deeply hands-on, with a mandate to operate with urgency and independence while remaining tightly integrated with biology, protein engineering, and translational science colleagues across the pod. Key Accountabilities 1. In Silico Biologics Design for Pod Programs Define and drive the computational design strategy across the pod's large-molecule programs, including antibody, VHH, and multispecific or fusion formats, from early format selection through lead optimization. Design and prioritize molecular candidates using generative AI/ML and computational modeling approaches Serve as a scientific advisor to pod leadership on computational design decisions, influencing program direction and key trade-offs Partner closely with the Biologics Discovery Lead to translate computational proposals into testable engineering priorities; challenge and be challenged on scientific assumptions in equal measure. Integrate structural biology data into design strategies to inform format selection, epitope targeting, and interface optimization. Oversee virtual screening, binding affinity prediction, and developability risk assessment for candidate sequences; provide ranked shortlists with quantified uncertainty to the pod. Establish and improve approaches to accelerate lead optimization by compressing DMTA cycles through AI-guided design, with the goal of achieving the target candidate profile in fewer rounds. Collaborate with translational and DMPK scientists to model PK/PD behavior, TMDD, and species cross-reactivity in silico, informing study design and reducing in vivo cycle time. 2. AI/ML Platform Interface and Data Strategy Serve as the pod's primary computational interface to Takeda's AI/ML research platform; evaluate and benchmark new AI design tools against the pod's specific biologics modalities and program needs. Define and steward data requirements for AI model training within the pod: structure data return from experimental campaigns, annotation standards, and integration with Takeda's data infrastructure. Contribute to building and curating AI/ML training datasets from pod experimental outputs to enable continuous model improvement. Guide development and refinement of computational workflows to enable pod scalability, speed and reproducibility across the DMTA cycle; document methods to support cross-pod learning. 3. Pod Integration and Scientific Operations Act as a hands-on computational authority within pod governance: prepare and present in silico analyses for PRC reviews, design review boards, and candidate declaration milestones. Ensure computational requirements are integrated early in external experimental campaigns to maximize data return value. Interface with Takeda's discovery automation capabilities to define assay and data readout specifications for pod programs entering automated workflows when applicable. 4. Scientific Leadership and External Engagement Maintain deep subject-matter expertise by staying current with advances in AI for biologics design and structure prediction; translate emerging capabilities into actionable proposals for the pod. Identify and translate relevant external innovations into opportunities that enhance pod capabilities and programs Represent Takeda's computational biologics capabilities in interactions with external partners, at conferences, and in the scientific community; contribute to publications and IP filings as appropriate. Provide scientific mentorship within the AIRx context and help shape computational biologics practices across the broader research organization. Qualifications & Competencies Expected Requirements: PhD in Computational Biology, Bioinformatics, Structural Biology, Computer Science, or a closely related discipline. 10+ years of drug discovery experience with a demonstrated track record of computational impact on large-molecule or biologics programs; industry experience strongly preferred. Deep expertise in antibody and protein sequence, structure, and function modeling, with proficiency in generative or predictive AI frameworks applied to biologics design. Broad proficiency in computational tools relevant to biologics, spanning structural analysis, molecular simulation, developability prediction, and bioinformatics. Strong coding skills (Python required); experience building and deploying ML models in a drug discovery context; familiarity with cloud-based compute and MLOps practices. Demonstrated ability to operate as both a technical individual contributor and a cross-functional scientific partner in a fast-paced, program-driven environment. Versatile communicator: able to present complex computational findings to biologists, clinical scientists, and senior leadership with clarity and scientific rigor. Preferred Experience with multispecific antibody formats and the associated engineering, developability, and PK/PD considerations. Experience integrating physics-based modeling with deep learning approaches to improve prediction accuracy and generalization. Prior experience defining data requirements and governance for AI/ML platform development across multiple programs or sites. Experience operating within or alongside an external AI design partner environment, including co-design workflows and campaign-level data return. Track record of contributing to IND-enabling programs; familiarity with candidate declaration criteria and biologics CMC considerations. ADDITIONAL INFORMATION The position will be based in Cambridge, MA. This position is currently classified as "hybrid" by Takeda's Hybrid and Remote Work policy Takeda Compensation and Benefits Summary We understand compensation is an important factor as you consider the next step in your career. We are committed to equitable pay for all employees, and we strive to be more transparent with our pay practices. For Location: Boston, MA U.S. Base Salary Range: $177,000.00 - $278,080.00 The estimated salary range reflects an anticipated range for this position. The actual base salary offered may depend on a variety of factors, including the qualifications of the individual applicant for the position, years of relevant experience, specific and unique skills, level of education attained, certifications or other professional licenses held, and the location in which the applicant lives and/or from which they will be performing the job. The actual base salary offered will be in accordance with state or local minimum wage requirements for the job location. U. xibtplm S. based employees may be eligible for short-term and/ or long-term incentives. U.S. based employees may be eligible to participate in medical, dental, vision insurance, a 401(k) plan and
Takeda Pharmaceutical
Cambridge, Massachusetts
By clicking the "Apply" button, I understand that my employment application process with Takeda will commence and that the information I provide in my application will be processed in line with Takeda's Privacy Notice and Terms of Use. I further attest that all information I submit in my employment application is true to the best of my knowledge. Read on to find out what you will need to succeed in this position, including skills, qualifications, and experience. Job Description Purpose / Overview Takeda is seeking a strategic and execution-focused Change Management leader to drive adoption and value realization for the Labs of Tomorrow initiative across Research. Reporting to the Head of Research Program Management, this role is accountable for ensuring that transformation efforts-including lab automation, digital enablement, and new operating models-are not only delivered, but adopted, embedded, and sustained to achieve measurable impact. This role operates as a peer to Labs of Tomorrow Program Managers, where the PMs own delivery and this role owns adoption, behavior change, and value realization. This is not a passive support role. The incumbent will drive change across the organization, challenge legacy ways of working, identify barriers to adoption, and ensure that transformation efforts result in measurable improvements in research productivity, operational efficiency, decision velocity, and organizational readiness. Key Responsibilities / Accountabilities Change Management Leadership Lead and drive change management strategies for the Labs of Tomorrow program that includes lab automation, digital enablement, new operating models, and future transformation workstreams. Define change impacts, stakeholder needs, adoption risks, and behavior changes required for successful implementation. Ensure all initiatives have clear adoption, readiness, and value realization plans. Adoption of New Ways of Working Drive adoption of new cultural pillars, behaviors, processes, tools, and organizational practices across Research. Partner with workstream leads and PM counterparts to ensure impacted teams understand what is changing, why it matters, and how success will be measured. Identify resistance, ambiguity, and adoption gaps early; develop and execute targeted interventions to maintain momentum. Stakeholder Engagement Enable leaders to act as visible sponsors of change, reinforcing new behaviors Act as a central change management partner across Research, Digital / IT, Operations, Quality, Finance, Communications, HR / Talent, and senior leadership. Build alignment across diverse stakeholder groups and ensure leaders actively sponsor and reinforce required changes. Serve as a trusted advisor to Labs of Tomorrow leaders on stakeholder readiness, change risks, and adoption strategy. Communications & Training Develop audience-specific communications strategies for senior leaders, scientific teams, lab users, enabling functions, and impacted stakeholders. Translate complex cross-functional transformation information into clear, practical, and digestible formats. Design and deliver training, playbooks, onboarding materials, workshops, town halls, and engagement sessions that build capability and accelerate adoption. Program Integration Work in peer partnership Labs of Tomorrow PMs to integrate change milestones, stakeholder dependencies, and adoption risks into broader program plans. Provide a "wide-angle lens" on cross-functional change impacts that may affect execution, adoption, or sustainability. Support governance materials and executive updates by clearly communicating adoption progress, change risks, decisions needed, and mitigation plans. Metrics & Continuous Improvement Ensure transformation efforts translate into measurable improvements in productivity, efficiency, and decision velocity. Define and monitor change adoption metrics, including readiness, engagement, behavior adoption, tool usage, training effectiveness, stakeholder sentiment, and realized impact. Conduct regular readiness assessments and use feedback to refine change interventions. Capture lessons learned and codify repeatable change management practices for future Labs of Tomorrow initiatives. Qualifications Education Sound scientific knowledge with Bachelor's degree 18 years, MS 16 years or PhD 10 years in Science or Management related discipline Expected of 5-7 years of change management experience with experience in early drug discovery (e.g., target identification, hit to-lead stages) and late drug discovery (e.g., candidate stage, preclinical/IND enabling stages) in the capacity as a program manager. Project Management Professional (PMP ) certification and/or Change Management certification (e.g., Prosci, CCMP) required Experience Experience in biopharma R&D, lab operations, digital transformation, automation, or research operations strongly preferred. Demonstrated experience interacting with senior executives and influencing cross-functional stakeholders in a matrixed environment. Strong understanding of organizational change management methodologies and practical application in complex scientific or technical environments. Experience developing stakeholder engagement plans, readiness assessments, communication strategies, training plans, and adoption metrics. Ability to integrate change management with project management disciplines, including planning, risk management, dependency tracking, milestone tracking, governance, and budget oversight. Strong analytical skills with the ability to interpret adoption data and translate insights into action. Familiarity with lab automation, digital workflow tools, R&D transformation, or change management platforms preferred. Leadership & Soft Skills Exceptional leadership, communication, facilitation, and stakeholder management skills. Ability to influence, negotiate, and build consensus across multiple levels of the organization. Comfortable challenging the status quo and driving adoption of new behaviors and operating practices. Proven problem-solving, analytical, and strategic planning capabilities. Strong executive presence with the ability to distill complex issues into clear recommendations. Entrepreneurial, proactive, and comfortable operating in ambiguity while creating structure for others. ADDITIONAL INFORMATION The position will be based in Cambridge, MA. Takeda Compensation and Benefits Summary We understand compensation is an important factor as you consider the next step in your career. We are committed to equitable pay for all employees, and we strive to be more transparent with our pay practices. For Location: Boston, MA U.S. Base Salary Range: $177,000.00 - $278,080.00 The estimated salary range reflects an anticipated range for this position. The actual base salary offered may depend on a variety of factors, including the qualifications of the individual applicant for the position, years of relevant experience, specific and unique skills, level of education attained, certifications or other professional licenses held, and the location in which the applicant lives and/or from which they will be performing the job. The actual base salary offered will be in accordance with state or local minimum wage requirements for the job location. U.S. based employees may be eligible for short-term and/ or long-term incentives. U.S. based employees may be eligible to participate in medical, dental, vision insurance, a 401(k) plan and company match, short-term and long-term disability coverage, basic life insurance, a tuition reimbursement program, paid volunteer time off, company holidays, and well-being benefits, among others. xibtplm U.S. based employees are also eligible to receive, per calendar year, up to 80 hours of sick time, and new hires are eligible to accrue up to 120 hours of paid vacation. EEO Statement Takeda is proud in its commitment to creating a diverse workforce and providing equal employment opportunities to all employees and applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, gender expression, parental status, national origin, age, disability, citizenship status, genetic information or characteristics, marital status, status as a Vietnam era veteran, special disabled veteran, or other protected veteran in accordance with applicable federal, state and local laws, and any other characteristic protected by law. LocationsBoston, MAWorker TypeEmployee
By clicking the "Apply" button, I understand that my employment application process with Takeda will commence and that the information I provide in my application will be processed in line with Takeda's Privacy Notice and Terms of Use. I further attest that all information I submit in my employment application is true to the best of my knowledge. Read on to find out what you will need to succeed in this position, including skills, qualifications, and experience. Job Description Purpose / Overview Takeda is seeking a strategic and execution-focused Change Management leader to drive adoption and value realization for the Labs of Tomorrow initiative across Research. Reporting to the Head of Research Program Management, this role is accountable for ensuring that transformation efforts-including lab automation, digital enablement, and new operating models-are not only delivered, but adopted, embedded, and sustained to achieve measurable impact. This role operates as a peer to Labs of Tomorrow Program Managers, where the PMs own delivery and this role owns adoption, behavior change, and value realization. This is not a passive support role. The incumbent will drive change across the organization, challenge legacy ways of working, identify barriers to adoption, and ensure that transformation efforts result in measurable improvements in research productivity, operational efficiency, decision velocity, and organizational readiness. Key Responsibilities / Accountabilities Change Management Leadership Lead and drive change management strategies for the Labs of Tomorrow program that includes lab automation, digital enablement, new operating models, and future transformation workstreams. Define change impacts, stakeholder needs, adoption risks, and behavior changes required for successful implementation. Ensure all initiatives have clear adoption, readiness, and value realization plans. Adoption of New Ways of Working Drive adoption of new cultural pillars, behaviors, processes, tools, and organizational practices across Research. Partner with workstream leads and PM counterparts to ensure impacted teams understand what is changing, why it matters, and how success will be measured. Identify resistance, ambiguity, and adoption gaps early; develop and execute targeted interventions to maintain momentum. Stakeholder Engagement Enable leaders to act as visible sponsors of change, reinforcing new behaviors Act as a central change management partner across Research, Digital / IT, Operations, Quality, Finance, Communications, HR / Talent, and senior leadership. Build alignment across diverse stakeholder groups and ensure leaders actively sponsor and reinforce required changes. Serve as a trusted advisor to Labs of Tomorrow leaders on stakeholder readiness, change risks, and adoption strategy. Communications & Training Develop audience-specific communications strategies for senior leaders, scientific teams, lab users, enabling functions, and impacted stakeholders. Translate complex cross-functional transformation information into clear, practical, and digestible formats. Design and deliver training, playbooks, onboarding materials, workshops, town halls, and engagement sessions that build capability and accelerate adoption. Program Integration Work in peer partnership Labs of Tomorrow PMs to integrate change milestones, stakeholder dependencies, and adoption risks into broader program plans. Provide a "wide-angle lens" on cross-functional change impacts that may affect execution, adoption, or sustainability. Support governance materials and executive updates by clearly communicating adoption progress, change risks, decisions needed, and mitigation plans. Metrics & Continuous Improvement Ensure transformation efforts translate into measurable improvements in productivity, efficiency, and decision velocity. Define and monitor change adoption metrics, including readiness, engagement, behavior adoption, tool usage, training effectiveness, stakeholder sentiment, and realized impact. Conduct regular readiness assessments and use feedback to refine change interventions. Capture lessons learned and codify repeatable change management practices for future Labs of Tomorrow initiatives. Qualifications Education Sound scientific knowledge with Bachelor's degree 18 years, MS 16 years or PhD 10 years in Science or Management related discipline Expected of 5-7 years of change management experience with experience in early drug discovery (e.g., target identification, hit to-lead stages) and late drug discovery (e.g., candidate stage, preclinical/IND enabling stages) in the capacity as a program manager. Project Management Professional (PMP ) certification and/or Change Management certification (e.g., Prosci, CCMP) required Experience Experience in biopharma R&D, lab operations, digital transformation, automation, or research operations strongly preferred. Demonstrated experience interacting with senior executives and influencing cross-functional stakeholders in a matrixed environment. Strong understanding of organizational change management methodologies and practical application in complex scientific or technical environments. Experience developing stakeholder engagement plans, readiness assessments, communication strategies, training plans, and adoption metrics. Ability to integrate change management with project management disciplines, including planning, risk management, dependency tracking, milestone tracking, governance, and budget oversight. Strong analytical skills with the ability to interpret adoption data and translate insights into action. Familiarity with lab automation, digital workflow tools, R&D transformation, or change management platforms preferred. Leadership & Soft Skills Exceptional leadership, communication, facilitation, and stakeholder management skills. Ability to influence, negotiate, and build consensus across multiple levels of the organization. Comfortable challenging the status quo and driving adoption of new behaviors and operating practices. Proven problem-solving, analytical, and strategic planning capabilities. Strong executive presence with the ability to distill complex issues into clear recommendations. Entrepreneurial, proactive, and comfortable operating in ambiguity while creating structure for others. ADDITIONAL INFORMATION The position will be based in Cambridge, MA. Takeda Compensation and Benefits Summary We understand compensation is an important factor as you consider the next step in your career. We are committed to equitable pay for all employees, and we strive to be more transparent with our pay practices. For Location: Boston, MA U.S. Base Salary Range: $177,000.00 - $278,080.00 The estimated salary range reflects an anticipated range for this position. The actual base salary offered may depend on a variety of factors, including the qualifications of the individual applicant for the position, years of relevant experience, specific and unique skills, level of education attained, certifications or other professional licenses held, and the location in which the applicant lives and/or from which they will be performing the job. The actual base salary offered will be in accordance with state or local minimum wage requirements for the job location. U.S. based employees may be eligible for short-term and/ or long-term incentives. U.S. based employees may be eligible to participate in medical, dental, vision insurance, a 401(k) plan and company match, short-term and long-term disability coverage, basic life insurance, a tuition reimbursement program, paid volunteer time off, company holidays, and well-being benefits, among others. xibtplm U.S. based employees are also eligible to receive, per calendar year, up to 80 hours of sick time, and new hires are eligible to accrue up to 120 hours of paid vacation. EEO Statement Takeda is proud in its commitment to creating a diverse workforce and providing equal employment opportunities to all employees and applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, gender expression, parental status, national origin, age, disability, citizenship status, genetic information or characteristics, marital status, status as a Vietnam era veteran, special disabled veteran, or other protected veteran in accordance with applicable federal, state and local laws, and any other characteristic protected by law. LocationsBoston, MAWorker TypeEmployee