Data Science Capability Lead

Financial Conduct Authority
Edinburgh
1 month ago
Applications closed

Related Jobs

View all jobs

Principal – Energy Consulting (Crude Oil and Refined Products - Downstream) (Basé à London)

Principal - Long Term Oil & Energy Consulting (Basé à London)

Head of Data Engineering

Senior Product Manager Omics (Basé à London)

Lead CRM Solution Architect - Microsoft Dynamics 365

Head Of Data Engineering (Basé à London)

Data Science Capability Lead

Division– Data, Technology & Innovation (DTI)

Department– Advanced Analytics

Salary– National – ranging from £59,100 – £80,000 and London from £64,900 – £90,000 per annum (salary offered will be based on skills and experience)

About the FCA

The FCA regulates the conduct of 45,000 firms in the UK to ensure our financial markets are honest, fair and competitive. Follow this link to find out moreAbout the FCA.

The Team/Department

The FCA’s Advanced Analytics department is seeking a Data Science Capability Lead, a pivotal role focused on developing and enhancing data science skills across the organisation. This position is crucial for nurturing a culture of continuous learning and elevating the technical and strategic capabilities of data scientists.

What will you be doing?

  • Leading hackathon-style events:Manage events across Advanced Analytics and the wider FCA to identify and develop cutting-edge data science techniques. These hackathons focus on creating rapid proof-of-concepts that explore innovative approaches and deliver actionable data.

  • Leading the Data Bootcamp Programme:Oversee the upskilling of approximately 60-100 managers and technical specialists annually in data analytics and insights. This programme is designed to deliver targeted, impactful learning experiences that enhance understanding of data tools and methodologies.

  • Overseeing learning and knowledge-sharing opportunities:Manage an internal suite of initiatives such as mentoring, reverse mentoring, Journal Clubs, and Kaggle competitions to foster a culture of continuous professional development.

  • Fostering data science community development:Create and maintain a vibrant data science community within the organisation, encouraging collaboration and sharing best practices.

  • Supporting the graduate pipeline:Facilitate the integration and growth of graduates within the organisation by providing mentorship and structured learning opportunities.

  • Ensuring effective tools and processes:Ensure that data scientists have the necessary tools and processes to perform their roles effectively, collaborating with the management team to enhance efficiency.

Which skills are required?

Minimum

  • Data Science expertise – Strong working knowledge of data science methodologies, analytics tools, and statistical techniques.

  • Leadership & mentorship – Proven experience in mentoring and coaching data scientists or analysts.

  • Stakeholder engagement – Ability to collaborate effectively with both technical and non-technical stakeholders.

Essential

  • Programme & event management – Experience in planning and running large-scale learning initiatives.

  • Project delivery – Ability to manage multiple initiatives simultaneously.

  • Supporting graduate & early career talent – Experience in mentoring or integrating graduates into data teams.

  • Building & nurturing a data science community – Demonstrated success in fostering collaboration among data scientists.

  • Optimising data science tools & processes – Track record of improving the efficiency of data science workflows.

  • Hands-on technical proficiency – Experience with Python, R, SQL, or other relevant data science tools.

  • Experience in regulatory environment – Understanding of data science applications within regulatory, financial, or governmental contexts.

  • Knowledge of AI & Machine Learning – Familiarity with emerging trends in AI, ML, and their practical applications.

Benefits of working at the FCA

  • 25 days holiday per year plus bank holidays.

  • Hybrid working (work from home up to 60% of your time).

  • Private healthcare with Bupa.

  • A non-contributory Pension of at least 8%.

  • Life assurance.

  • Income protection.

We welcome applications from candidates who are looking for flexible arrangements.

Application Support

We are dedicated to removing barriers and ensuring our application process is accessible to everyone.

Useful Information and Timeline

  • Advert closing date: Sunday 30th March.

  • CV review/shortlist: w/c 31st March.

  • Interview to assess technical capability and core skills: w/c 7th April.

Got a question?

If you are interested in learning more about the role, please contact: Melanie Dubock at

Applications must be submitted through our online portal. Applications sent via email will not be accepted.

#J-18808-Ljbffr

Get the latest insights and jobs direct. Sign up for our newsletter.

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

Industry Insights

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

Jobs

Contract vs Permanent Machine Learning Jobs: Which Pays Better in 2025?

Machine learning (ML) has swiftly become one of the most transformative forces in the UK technology landscape. From conversational AI and autonomous vehicles to fraud detection and personalised recommendations, ML algorithms are reshaping how organisations operate and how consumers experience products and services. In response, job opportunities in machine learning—including roles in data science, MLOps, natural language processing (NLP), computer vision, and more—have risen dramatically. Yet, as the demand for ML expertise booms, professionals face a pivotal choice about how they want to work. Some choose day‑rate contracting, leveraging short-term projects for potentially higher immediate pay. Others embrace fixed-term contract (FTC) roles for mid-range stability, or permanent positions for comprehensive benefits and a well-defined career path. In this article, we will explore these different employment models, highlighting the pros and cons of each, offering sample take‑home pay scenarios, and providing insights into which path might pay better in 2025. Whether you’re a new graduate with a machine learning degree or an experienced practitioner pivoting into an ML-heavy role, understanding these options is key to making informed career decisions.

Jobs

Machine‑Learning Jobs for Non‑Technical Professionals: Where Do You Fit In?

The Model Needs More Than Math When ChatGPT went viral and London start‑ups raised seed rounds around “foundation models,” many professionals asked, “Do I need to learn PyTorch to work in machine learning?” The answer is no. According to the Turing Institute’s UK ML Industry Survey 2024, 39 % of advertised ML roles focus on strategy, compliance, product or operations rather than writing code. As models move from proof‑of‑concept to production, demand surges for specialists who translate algorithms into business value, manage risk and drive adoption. This guide reveals the fastest‑growing non‑coding ML roles, the transferable skills you may already have, real transition stories and a 90‑day action plan—no gradient descent necessary.

Careers Jobs

Quantexa Machine‑Learning Jobs in 2025: Your Complete UK Guide to Joining the Decision‑Intelligence Revolution

Money‑laundering rings, sanctioned entities, synthetic identities—complex risks hide in plain sight inside data. Quantexa, a London‑born scale‑up now valued at US $2.2 bn (Series F, August 2024), solves that problem with contextual decision‑intelligence (DI): graph analytics, entity resolution and machine learning stitched into a single platform. Banks, insurers, telecoms and governments from HSBC to HMRC use Quantexa to spot fraud, combat financial crime and optimise customer engagement. With the launch of Quantexa AI Studio in February 2025—bringing generative AI co‑pilots and large‑scale Graph Neural Networks (GNNs) to the platform—the company is hiring at record pace. The Quantexa careers portal lists 450+ open roles worldwide, over 220 in the UK across data science, software engineering, ML Ops and client delivery. Whether you are a graduate data scientist fluent in Python, a Scala veteran who loves Spark or a solutions architect who can turn messy data into knowledge graphs, this guide explains how to land a Quantexa machine‑learning job in 2025.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.