Data Scientist creating machine learning solutions to detect financial crime at a significant financial institution. Leading model development with business stakeholders and engineers while maintaining compliance standards.
About the role
- Lead Data Scientist applying advanced analytics to combat financial crime at FCA. Guiding a team of data scientists and collaborating with partners to drive strategic initiatives.
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
Requirements
- 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
- 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
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
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