Clinical Data Scientist

PSI CRO
Oxford
1 year ago
Applications closed

Related Jobs

View all jobs

Data Scientist (Predictive Modelling) – NHS

Data Scientist (Predictive Modelling) – NHS

Principal, AI Data Scientist

Data science programme lead

Data science programme lead

Data science programme lead

Job Description

Reporting to the Clinical Data Science Manager, the Clinical Data Scientist is an integral part of our team here at PSI. You will work with clinical trials patient and operational data, develop new data solutions and set up Risk-based Monitoring systems in Process Improvement department.

Hybrid work in Oxford

  • Participate in selection of the Risk-Based Monitoring (RBM) system and provide relevant training to the project team and/or Sponsor
  • Set up and maintain RBM systems, collaborating with the Central Monitoring Manager
  • Manage complex datasets from multiple sources, including data extraction, transformation, and loading into PSI data platform
  • Program and produce data listings, tables, and figures for Clinical Data Reviewers and Central Monitoring Managers
  • Calculate Key Risk Indicators and Quality Tolerance Limits, applying advanced analytical techniques to identify data trends for Centralized Monitoring
  • Collaborate cross-functionally to identify study challenges and develop data solutions using advanced analytics
  • Communicate data findings and solutions to stakeholders effectively
  • Contribute to the development of databases, software products, processes, and Quality System Documents for Centralized Monitoring


Qualifications

Must have:

  • Degree in Data Science, Mathematics, Statistics, Computer Science or equivalent; or relevant work experience and professional qualifications
  • At least 5 years of experience in Data Management, Biostatistics, and Centralized Monitoring
  • At least 4 years of experience in one or more of the following: R, R Shiny, SAS, SQL and associated packages and libraries
  • At least 2-year experience in data engineering area including one or more of the following: relationship databases, data warehousing, data schemas, data stores, data modeling, testing, validation and analysis
  • Full professional proficiency in English
  • Strong analytical an logical thinking
  • Communication and collaboration skills

Nice to have:

  • Experience with CluePoints RBM system
  • Knowledge of statistical methods and techniques for analyzing data
  • Experience with using Machine Learning technics and products testing and validation



Additional Information

What we offer:

  • We value your time so the recruitment process is as quick as 3 meetings
  • We'll prepare you to do your job at highest quality level with our extensive onboarding and mentorship program
  • You'll have excellent working conditions - spacious and modern office in convenient location, and friendly, supportive team who love to hang out together 
  • You'll have permanent work agreement at a stable, privately owned company
  • We care about our employees - aside from competitive salary, you'll have good work-life balance with flexible working hours and additional days off, life and medical insurance, sports card, lunch card 
  • We're constantly growing which means opportunities for personal and professional growth 

Make the right call and take your career to a whole new level. Join the company that focuses on its people and invests in their professional development and success.

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.