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

Apply Now

Lead Data Scientist

Financial Conduct Authority
Edinburgh
1 week ago
Create job alert
Overview

Lead Data Scientist


Division – Intelligence & Digital


Department – Advanced Analytics and Data Science Units


This role sits in a Data Science team which supports the FCA Enforcement and the Financial Crime agenda. In this role, you will be applying cutting-edge AI and advanced analytics to support the FCA in its fight against financial crime.


Role responsibilities

  • Support and guide a team of data scientists through thoughtful mentorship, regular feedback and career development conversations that nurture individual growth.


  • Cultivate a collaborative and curious team environment by encouraging exploration of new tools, techniques and approaches in data science.


  • Build strong relationships with internal partners to co-design data science projects that reflect regulatory priorities and contribute meaningfully to strategic goals.


  • Take a proactive role in shaping and leading initiatives within the Enforcement & Financial Crime Data Science Unit, helping drive progress on impactful programmes.


  • Work closely with data engineering and governance colleagues to ensure data pipelines are secure, scalable and designed to meet evolving needs.


  • Champion excellence in data science by promoting best practices, conducting supportive code reviews and contributing to efforts that enhance financial crime detection and enforcement.



Skills

Minimum:



  • Experience in Python, R or other object-oriented languages, applying diverse data science techniques.


  • Experience of leading key workstreams within complex, cross-functional projects, collaborating with stakeholders and ensuring appropriate resourcing to deliver outcomes.


  • Experience of collaborating with data engineering and governance teams to maintain and optimise data pipelines.



Essential:



  • Skilled in designing and delivering analytics projects using large, structured and unstructured datasets.


  • Effective collaboration with technical and non-technical stakeholders to develop solutions.


  • Experience in project leadership, managing, mentoring and developing junior data scientists.


  • Clear communication of insights to stakeholders.



Salary and grading

  • Salary: National (Edinburgh and Leeds) ranging from £59,100 to £80,233 and London from £64,900 to £88,100 (salary offered will be based on skills and experience).


  • This role is graded as: Lead Associate - Regulatory.



For applicants

  • Your recruitment contact is Benjamin via . Applications must be submitted through our online portal. Applications sent via social media or email will not be accepted.


  • Disability Confident: Our hiring approach. We’re proud to be a Disability Confident Employer, and therefore, people with disabilities and long-term conditions who best meet the minimum criteria for a role will go through to the next stage of the recruitment process. In cases of high application volumes we may progress applicants whose experience most closely matches the role’s key requirements.



Benefits

  • 25 days annual leave plus bank holidays.


  • Hybrid model with up to 60% remote work.


  • Non-contributory pension (8–12% depending on age) and life assurance at eight times your salary.


  • Private healthcare with Bupa, income protection, and 24/7 Employee Assistance.


  • 35 hours of paid volunteering annually.


  • A flexible benefits scheme designed around your lifestyle.



For a full list of our benefits, and our recruitment process as a whole visit our benefits page.


Our values & culture

Our colleagues are the key to our success as a regulator. We are committed to fostering a diverse and inclusive culture: one that’s free from discrimination and bias, celebrates difference, and supports colleagues to deliver at their best. We believe that our differences and similarities enable us to be a better organisation – one that makes better decisions, drives innovation, and delivers better regulation.


If you require any adjustments due to a disability or condition, your recruiter is here to help - reach out for tailored support. We welcome diverse working styles and aim to find flexible solutions that suit both the role and individual needs, including options like part-time and job sharing where applicable.


Disability confidence and recruitment

We’re proud to be a Disability Confident Employer, and therefore, people with disabilities and long-term conditions who best meet the minimum criteria for a role will go through to the next stage of the recruitment process. In cases of high application volumes we may progress applicants whose experience most closely matches the role’s key requirements.


Useful information and timelines

  • Advert Closing Date: 9 November at 11:59pm.


  • CV Review/Shortlist: 10–11 November.


  • Interviews: from 17th November.



Your Recruiter will discuss the process in detail with you during screening for the role; please make them aware if you are going to be unavailable for any date during this time.


SC Clearance is required for this role (SC Guidance) - you will hold or will be required to obtain Security Check (SC) level vetting.


#J-18808-Ljbffr

Related Jobs

View all jobs

Lead Data Scientist

Lead Data Scientist

Lead Data Scientist

Lead Data Scientist and Machine Learning Lead

Lead Data Scientist - Full Time

Lead Data Scientist - Banking

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.