Engineer the Quantum RevolutionYour expertise can help us shape the future of quantum computing at Oxford Ionics.

View Open Roles

Senior Data Scientist

Faculty
London
2 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Scientist - Computer Vision

Senior Data Scientists

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

About Faculty

At Faculty, we transform organisational performance through safe, impactful and human-centric AI.

With a decade of experience, we provide over 300 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.

We operate a hybrid way of working, meaning that you'll split your time across client location, Faculty's Old Street office and working from home depending on the needs of the project. For this role, you can expect to be client-side for up-to three days per week at times and working either from home or our Old street office for the rest of your time.

What you'll be doing:

As a Senior Data Scientist in our Defence business unit you will lead project teams that deliver bespoke algorithms to our clients across the defence and national security sector. 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.

You will play an important role in the development of others at Faculty by acting as the designated mentor of a small number of data scientists, and by supporting the professional growth of data scientists on the project team. The latter includes giving targeted support where needed, and providing step-up opportunities where helpful.

Faculty has earned wide recognition as a leader in practical data science. You will actively contribute to the growth of this reputation by delivering courses to high-value clients, by talking at major conferences, by participating in external roundtables, or by contributing to large-scale open-source projects. You will also have the opportunity to teach on the fellowship about topics that range from basic statistics to reinforcement learning, and to mentor the fellows through their 6-week project.

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:

  • Senior 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
  • A leadership mindset focussed on growing the technical capabilities of the team; a caring attitude towards the personal and professional development of other data scientists; enthusiasm for nurturing a collaborative and dynamic culture
  • 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

What we can offer you:

The Faculty team is diverse and distinctive, and we all come from different personal, professional and organisational backgrounds. We all have one thing in common: we are driven by a deep intellectual curiosity that powers us forward each day.

Faculty is the professional challenge of a lifetime. You'll be surrounded by an impressive group of brilliant minds working to achieve our collective goals.

Our consultants, product developers, business development specialists, operations professionals and more all bring something unique to Faculty, and you'll learn something new from everyone you meet.


#J-18808-Ljbffr

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.

Seasonal Hiring Peaks for Data Science Jobs: The Best Months to Apply & Why

The UK's data science sector has matured into one of Europe's most intellectually rewarding and financially attractive technology markets, with roles spanning from junior data analysts to principal data scientists and heads of artificial intelligence. With data science positions commanding salaries from £30,000 for graduate data analysts to £140,000+ for senior principal scientists, understanding when organisations actively recruit can dramatically accelerate your career progression in this intellectually stimulating and rapidly evolving field. Unlike traditional analytical roles, data science hiring follows distinct patterns influenced by business intelligence cycles, research funding schedules, and machine learning project timelines. The sector's unique combination of mathematical rigour, business impact requirements, and cutting-edge technology adoption creates predictable hiring windows that strategic professionals can leverage to advance their careers in extracting insights from tomorrow's data. This comprehensive guide explores the optimal timing for data science job applications in the UK, examining how enterprise analytics strategies, academic research cycles, and artificial intelligence initiatives influence recruitment patterns, and why strategic timing can determine whether you join a pioneering AI research team or miss the opportunity to develop the next generation of intelligent systems.

Pre-Employment Checks for Data Science Jobs: DBS, References & Right-to-Work and more Explained

Pre-employment screening in data science reflects the discipline's unique position at the intersection of statistical analysis, machine learning innovation, and strategic business intelligence. Data scientists often have privileged access to comprehensive datasets, proprietary algorithms, and business-critical insights that form the foundation of organisational strategy and competitive positioning. The data science industry operates within complex regulatory frameworks spanning GDPR, sector-specific data protection requirements, and emerging AI governance regulations. Data scientists must demonstrate not only technical competence in statistical modelling and machine learning but also deep understanding of research ethics, data privacy principles, and the societal implications of algorithmic decision-making. Modern data science roles frequently involve analysing personally identifiable information, financial data, healthcare records, and sensitive business intelligence across multiple jurisdictions and regulatory frameworks simultaneously. The combination of analytical privilege, predictive capabilities, and strategic influence makes thorough candidate verification essential for maintaining compliance, security, and public trust in data-driven insights and automated systems.

Why Now Is the Perfect Time to Launch Your Career in Data Science: The UK's Analytics Revolution

The United Kingdom stands at the forefront of a data science revolution that's reshaping how businesses make decisions, governments craft policies, and society tackles its greatest challenges. From the machine learning algorithms powering London's fintech innovation to the predictive models guiding Manchester's smart city initiatives, Britain's transformation into a data-driven economy has created an unprecedented demand for skilled data scientists that far outstrips the available talent. If you've been contemplating a career transition or seeking to position yourself at the cutting edge of the digital economy, data science represents one of the most intellectually stimulating, financially rewarding, and socially impactful career paths available today. The convergence of big data maturation, artificial intelligence mainstream adoption, business intelligence evolution, and cross-industry digital transformation has created the perfect conditions for data science career success.