Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

UCI Policy Data Scientist (Fixed Term)

University of Cambridge
Cambridge
5 days ago
Create job alert
Overview

Join UCI at a pivotal time to impact the future of university commercialisation data & evidence for policy. The Policy Evidence Unit for University Commercialisation and Innovation (UCI) is a leading UK centre of excellence dedicated to improving the data, evidence and insights available to governments, funding agencies and universities to help them drive a step‑change in university contributions to innovation through commercialisation and knowledge exchange.


Funded by Research England (UKRI) since 2020, UCI has developed novel data, metrics and evidence on commercialisation and knowledge exchange, informing government policy and university practice.


We are looking for a motivated and collaborative Data Scientist to lead strategically important, data‑driven projects throughout 2026, supporting our long‑standing partnership with Research England.


Responsibilities

  • Expand the new university Spinout Register by integrating new data sources such as patents, people, funding, deal terms and investment.
  • Build a comprehensive database of patents linked to UK universities.
  • Develop tools to systematically extract, interrogate and analyse text‑based information from websites, documents, grants, etc., on the approaches universities use to support commercialisation and wider forms of knowledge exchange.

Qualifications

  • Strong interest in research commercialisation, knowledge/technology transfer or innovation processes and experience with research and innovation‑related data (grants, patents, publications).
  • Proficiency in one or more programming languages (e.g. R, Python).
  • Expertise in data extraction, integration, analysis and visualisation tools, pipeline development (APIs), and version control (e.g. Git).
  • Advanced skills in AI/ML and other analytical techniques to extract relevant insights from data.
  • Strong problem‑solving skills, analytical mindset and a solutions‑focused approach.
  • Excellent project scoping, planning and delivery abilities, translating user needs into tangible, milestone‑driven implementation plans.
  • Excellent interpersonal, networking and communication skills to work collaboratively in teams and convey complex methodologies to non‑technical audiences.
  • Ability to work independently and in teams within an environment with limited existing processes, developing novel methods, workflows and protocols from scratch to ensure reproducibility and scalability.

Benefits & Details

This is a 12‑month fixed‑term position ending 31 December 2026. The preferred start date is January 2026, with interviews scheduled during the week commencing 15 December 2025. Applications are welcome from internal candidates via secondment.


To apply, click the “Apply” button below to register an account with our recruitment system. If you have any questions about this vacancy or the application process, please contact the HR Office at the Department of Engineering: (01223 332615). Informal enquiries may be directed to Tomas Ulrichsen, Director of UCI, at .


Please quote reference NM47879 on your application and in any correspondence about this vacancy.


The University actively supports equality, diversity and inclusion and encourages applications from all sections of society. The University has a responsibility to ensure that all employees are eligible to live and work in the UK.


#J-18808-Ljbffr

Related Jobs

View all jobs

UCI Policy Data Scientist (Fixed Term)

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.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.