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Faculty

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Data Scientist - Fixed Term Contract

London - Hybrid

Job Description

Why Faculty?


We established Faculty in 2014 because we thought that AI would be the most important technology of our time. Since then, we’ve worked with over 350 global customers to transform their performance through human-centric AI. You can read about our real-world impact here.

We don’t chase hype cycles. We innovate, build and deploy responsible AI which moves the needle - and we know a thing or two about doing it well. We bring an unparalleled depth of technical, product and delivery expertise to our clients who span government, finance, retail, energy, life sciences and defence.

Our business, and reputation, is growing fast and we’re always on the lookout for individuals who share our intellectual curiosity and desire to build a positive legacy through technology.

AI is an epoch-defining technology, join a company where you’ll be empowered to envision its most powerful applications, and to make them happen.

This will be a fixed-term contract that should run until March 29th, 2026.

Why now?

We're in a period of significant growth, expanding our capacity to serve a diverse range of customers and apply AI to real-world problems with tangible impact. To meet this demand and maintain our high standards of delivery, we need skilled Data Scientists to join us for a temporary period and own end-to-end project delivery, build strong customer relationships, and help us scale our business.


What you'll be doing:

As a Data Scientist in our Applied AI team unit you will be part of project teams that deliver bespoke algorithms to our clients across a range of different sectors. You will be responsible for conceiving the data science approach, for designing the associated software architecture, and for ensuring that best practices are followed throughout.

You will help our excellent commercial team build strong relationships with clients, shaping the direction of both current and future projects. Particularly in the initial stages of commercial engagements, you will guide the process of defining the scope of projects to come with an emphasis on technical feasibility. We consider this work as fundamental towards ensuring that Faculty can continue to deliver high-quality software within the allocated timeframes.

Thanks to Faculty platform, you will have access to powerful computational resources, and you will enjoy the comforts of fast configuration, secure collaboration and easy deployment. Because your work in data science will inform the development of our AI products, you will often collaborate with software engineers and designers from our dedicated product team.

Who we're looking for:

  • Proven experience in either a professional data science position or a quantitative academic field

  • Strong programming skills as evidenced by earlier work in data science or software engineering. Although your programming language of choice (e.g. R, MATLAB or C) is not important, we do require the ability to become a fluent Python programmer in a short timeframe

  • An excellent command of the basic libraries for data science (e.g. NumPy, Pandas, Scikit-Learn) and familiarity with a deep-learning framework (e.g. TensorFlow, PyTorch, Caffe)

  • A high level of mathematical competence and proficiency in statistics

  • A solid grasp of essentially all of the standard data science techniques, for example, supervised/unsupervised machine learning, model cross validation, Bayesian inference, time-series analysis, simple NLP, effective SQL database querying, or using/writing simple APIs for models. We regard the ability to develop new algorithms when an innovative solution is needed as a fundamental skill

  • An appreciation for the scientific method as applied to the commercial world; a talent for converting business problems into a mathematical framework; resourcefulness in overcoming difficulties through creativity and commitment; a rigorous mindset in evaluating the performance and impact of models upon deployment

  • Some commercial experience, particularly if this involved client-facing work or project management; eagerness to work alongside our clients; business awareness and an ability to gauge the commercial value of projects; outstanding written and verbal communication skills; persuasiveness when presenting to a large or important audience

  • Experience leading a team of data scientists (to deliver innovative work according to a strict timeline) as well as experience in composing a project plan, in assessing its technical feasibility, and in estimating the time to delivery

Our Interview Process

For our fixed term requirements, we will run a shorter interview process

  1. Talent Team Screen (30 mins)

  2. Take home test

  3. Technical and Commercial focused interview (60mins)

Our Recruitment Ethos

We aim to grow the best team - not the most similar one. We know that diversity of individuals fosters diversity of thought, and that strengthens our principle of seeking truth. And we know from experience that diverse teams deliver better work, relevant to the world in which we live. We’re united by a deep intellectual curiosity and desire to use our abilities for measurable positive impact. We strongly encourage applications from people of all backgrounds, ethnicities, genders, religions and sexual orientations.

Some of our standout benefits:

  • Unlimited Annual Leave Policy

  • Private healthcare and dental

  • Enhanced parental leave

  • Family-Friendly Flexibility & Flexible working

  • Sanctus Coaching

  • Hybrid Working (2 days in our Old Street office, London)

If you don’t feel you meet all the requirements, but are excited by the role and know you bring some key strengths, please do apply or reach out to our Talent Acquisition team for a confidential chat - talent@faculty.ai Please know we are open to conversations about part-time roles or condensed hours.

Please mention that you found this job on MoAIJobs, this helps us grow. Thank you!

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About the job

Posted on

Dec 2, 2025

Apply before

Jan 1, 2026

Job typeFull-time
CategoryData Science

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