Natural Language Processing Data Scientist

  • Harnham
  • Feb 15, 2019
Python Java Data Scientist

Job Description

Harnham
Harnham

Machine Learning Engineer - Natural Language Processing

OXFORDSHIRE

£40,000 - £90,000

INTRODUCTION

We are working with an internationally recongised client based in Oxfordshire, who are looking to build out a team of NLP Research Data Scientists to help developing their current SaaS product offering. The problems are centred entirely around NLP, Sentiment Analysis and Deep Learning.

THE COMPANY

Our client are global leaders within academic publishing, but might just be on of the biggest companies you have never heard of! Off the back of their recent partnerships with major brands, they are looking to expand their Data Science team and further develop their product offering.

THE ROLE

This position is a good fit for all ranges of experience, but NLP and Deep Learning is at the core of the work. The challenge for anyone joining the team is to balance multiple porjects on the go simultaneously, all the way from Proof of Concept through to production.

YOUR SKILLS AND EXPERIENCE

As a Data Scientist the remit and requirements are as follows:

  • A passion for Data Science and Machine Learning
  • Strong development skills in Python or Java
  • Experience in developing machine learning and deep learning solutions and products
  • Deep understanding and experience in Text Mining and Natural Language Processing (NLP)
  • Experience with Keras, TensorFlow, PyTorch, sklearn, liblinear, Weka, or OpenNLP etc.
  • Proven ability to train, tune and evaluate ML models
  • Academic background in Computer Science or Machine Learning related fields
  • Team player who enjoys working collaboratively

THE BENEFITS

  • Competitive salary
  • Contributory pension scheme
  • Opportunity to grow in a fast-moving and dynamic organisation with like-minded colleagues.

HOW TO APPLY

To find out more about this opportunity and the other Data Science opportunities that we are representing at Harnham please apply via the link below or contact Mark Proud directly ()