Lead Data Scientist
Data & Analytics Engineering
Role Overview
We are recruiting a Lead Data Scientist to join a high-impact Data & Analytics Engineering function, focused on using advanced analytics, machine learning, and AI to drive measurable business outcomes across a financial services environment.
This role partners closely with stakeholders across product, pricing, underwriting, clinical review, and technology teams, as well as agile analytics squads delivering AI-enabled use cases. The successful candidate will play a key role in designing, developing, and monitoring predictive models and intelligent solutions that support strategic decision-making, risk assessment, and process automation. You will also help champion a data-driven culture built on sound governance and responsible AI practices.
Key Responsibilities
- Apply advanced data science and machine learning techniques to address complex business challenges, including predictive analytics, statistical modelling, data visualisation, and exploratory data analysis
- Design, build, and maintain scalable predictive models and AI-driven solutions that meet performance, quality, and governance standards
- Leverage structured and unstructured data sources from across the business and external providers to generate insights and enhance model effectiveness
- Contribute to the development and improvement of modelling methodologies, frameworks, and best practices
- Analyse model outputs and translate findings into clear, actionable recommendations for technical and non-technical stakeholders
- Support initiatives focused on automating and optimising decision-making processes through advanced analytics
- Promote best practices around model monitoring, validation, and risk-based decision-making
Skills & Experience Required
- Strong foundation in statistics, data science, and machine learning, including experience with predictive modelling, experimentation (A/B testing), and data visualisation
- Proficiency in data science and analytics languages and tools such as Python, R, and SQL, with experience working across varied data environments
- Hands-on experience with modern machine learning frameworks and libraries
- Solid understanding of data governance, model risk management, compliance, and security principles
- Strong commercial awareness, with the ability to align analytics work to business objectives and outcomes
- Excellent problem-solving and communication skills, with the ability to explain complex technical concepts to non-technical audiences
- Degree in a quantitative or technical discipline such as computer science, mathematics, statistics, or actuarial science
- 5+ year's experience designing, developing, and deploying data science or machine learning solutions in a production environment
Desirable Experience
- Background within financial services or insurance environments
- Experience using generative AI, including prompt engineering, retrieval-augmented generation (RAG), and integrating large language models into business workflows
- Familiarity with MLOps practices, including model deployment, monitoring, versioning, and lifecycle management
If this role suits you or someone in your network, feel free to reach out for a confidential chat.
GCS is acting as an Employment Business in relation to this vacancy.
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