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

Apply Now

Faculty Fellowship Programme Data Science (January 2026)

Faculty
Harrow
2 days ago
Create job alert
Faculty Fellowship Programme Data Science (January 2026)

Be among the first 25 applicants.

About Faculty

Faculty transforms organisational performance through safe, impactful and human‑centric AI. With more than a decade of experience, we provide over 350 global customers with software, bespoke AI consultancy and fellows from our award‑winning Fellowship programme. Our expert team brings together leaders from across government, academia and global tech giants to solve the biggest challenges in applied AI. Should you join us, you’ll have the chance to work with and learn from some of the brilliant minds who are bringing frontier AI to the frontlines of the world.

About The Fellowship

Artificial Intelligence is the most important technology of our age, but it is only valuable when it is applied in the real world. Since 2014, Faculty has helped 400+ PhD graduates, post‑doctoral researchers, masters and experienced software engineers transition into a career in data science through our Fellowship programme.

The Faculty Fellowship programme helps academics become highly‑skilled data scientists and machine learning engineers, transitioning successfully into careers and industries that are ready to benefit from artificial intelligence. After two weeks of intensive lectures and workshops, fellows learn how to apply their technical knowledge towards the application of data science, and are paired with project companies for a seven‑week data‑science project, during which they are paid the London Living Wage. The finale of the fellowship is Demo Day, where fellows present their work to an audience of 100+ guests and network with hiring managers and influential individuals from leading companies across London, the UK and Europe.

Requirements
  • You must have the right to work full‑time in the UK. We cannot sponsor this role.
  • PhD or Master’s in a STEM subject with some data science/machine‑learning experience.
  • High level of mathematical competence.
  • Programming experience, especially in Python.
  • Familiarity with statistical learning concepts (e.g. hypothesis testing, Bayesian inference, regression, SVM, random forests, neural networks, NLP, optimisation).
  • Experience with commonly used data‑science libraries.
  • Strong communication skills.
  • Ability to plan and meet self‑imposed deadlines.
Timelines
  • Submit application no later than Wednesday 5th November 2025 at 17:00 GMT.
  • Coding test in October 2025 (details via email).
  • Interviews mid‑November 2025 via Google Meet (details via email).
  • Decision communicated by January 9th 2026.
  • Programme runs Monday 26th Jan – Friday 27th Mar 2026, full‑time, London. Dates are tentative and may change.
Benefits
  • Paid London Living Wage for the full nine weeks.
  • Two weeks of training at the beginning of the fellowship are free.
  • Post‑programme alumni network and career support.
What We Offer

Faculty is a professional challenge of a lifetime. You’ll be surrounded by an impressive group of brilliant minds working to achieve our collective goals across product development, operations, and more. We value deep intellectual curiosity and diversity of background.


#J-18808-Ljbffr

Related Jobs

View all jobs

Faculty Fellowship Programme Data Science (January 2026)

Faculty Fellowship Programme Data Science (January 2026)

Senior Data Scientist

Lead Data Scientist - Customer Development

Senior Data Scientist - Retail and Consumer

Data Scientist - Retail and Consumer

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.