Senior Data Scientist
Made Tech
Sourced from Made Tech's careers site · verified 1 hour ago
Your role at Made Tech
As a Senior Data Scientist, you will work closely with clients and multidisciplinary teams to understand problems, explore possible approaches and deliver useful outcomes. Depending on the project, you might:
- investigate a service or policy problem and identify how data science or AI could help;
- analyse complex or imperfect data and communicate what it can and cannot tell us;
- prototype, build and evaluate statistical, machine-learning or AI systems;
- design and evaluate systems using large language models, retrieval, tools or agentic workflows;
- establish appropriate boundaries between model-driven behaviour, deterministic software and human decision-making;
- develop evaluation approaches, test cases and measures of success;
- help turn experimental work into reliable, maintainable services;
- advise clients on the responsible and proportionate use of data and AI;
- support clients to develop their own data science capability.
Skills, Knowledge & Expertise
- Applying data science, machine learning or AI to real problems and delivering useful outcomes.
- Framing ambiguous problems, identifying what evidence is needed and defining appropriate measures of success.
- Selecting methods based on the problem, available data, assumptions, risks and delivery context.
- Understanding statistical and machine-learning approaches well enough to use them appropriately, interpret their outputs and recognise their limitations.
- Establishing useful baselines and comparing complex approaches with simpler alternatives.
- Working confidently in Python and following good software development practices, including version control, testing, code review and reproducible development.
- Exploring, cleaning and assessing data, including identifying limitations, quality problems and potential sources of bias.
- Implementing robust evaluations using appropriate metrics, test cases, error analysis and qualitative investigation.
- Considering performance beyond aggregate accuracy, including reliability, uncertainty, fairness, security, cost and the consequences of failure.
- Developing or evaluating AI systems built around large language models, such as systems using structured outputs, retrieval, tool use or agentic workflows.
- Working with data engineers and software engineers to integrate data science or AI components into maintainable services.
- Communicating technical findings, uncertainty and trade-offs clearly to clients, users and multidisciplinary teams.
- Working directly with clients and building constructive relationships with people from different professional backgrounds.
- Mentoring colleagues, sharing knowledge and giving thoughtful technical feedback.
- Learning new techniques and technologies when they are useful, while applying appropriate scepticism to emerging approaches.
- working in a consultancy or other client-facing environment;
- working within government or the wider public sector;
- working on services where decisions have significant consequences for users;
- taking machine learning or AI systems beyond an initial prototype;
- evaluating, monitoring or assuring production AI systems;
- working with cloud platforms and modern deployment environments;
- working with APIs, data pipelines and production software systems;
- applying privacy, security, accessibility, fairness or responsible-AI considerations;
- working in multidisciplinary agile teams;
- line management, coaching or contributing to the development of a professional practice.
Job Benefits
- antiracist-activists
- disability
- lgbtqiaplus-allies-and-activists
- neurodiversity
- parents-carers
- women-in-tech
Compensation (from employer):
£49,500 - £75,000 / year
Skills
- data science
- machine learning
- AI
- problem framing
- success measures
- method selection
- statistics
- baselines
- Python
- version control
- testing
- code review
- reproducible development
- data exploration
- data cleaning
- data quality assessment
- bias identification
- evaluation metrics
- test cases
- error analysis
- qualitative investigation
- reliability
- uncertainty
- fairness
- security
- cost analysis
- large language models
- structured outputs
- retrieval
- tool use
- agentic workflows
- service integration
- client communication
- client relationships
- mentoring
- knowledge sharing
- technical feedback
- consultancy
- client-facing delivery
- government
- public sector
- high-consequence services
- production machine learning
- production AI
- AI evaluation
- AI monitoring
- AI assurance
- cloud platforms
- deployment environments
- APIs
- data pipelines
- production software systems
- privacy
- accessibility
- responsible AI
- agile
- line management
- coaching
- professional practice development
- generative AI
- natural language processing
- agentic systems
Summary
Deliver and evaluate data science and AI solutions for public sector clients, advising teams and mentoring colleagues.
Job title
Senior Data Scientist
Experience level
senior level
Industry
software
Location
Bristol, UK · Hybrid
+ 3 more locations
- London, UK · Hybrid
- Manchester, UK · Hybrid
- Swansea, UK · Hybrid
As listed by the employer.
Salary
£50k–£75k
Listed in the job description
Management role
Yes
- Oct 8, 2026 First posted
- Oct 8, 2026 Live now
As observed on the employer's careers site by ApplyAll. We show every change we've seen including removals.
Posting history
- Oct 8, 2026 First posted
- Oct 8, 2026 Live now
As observed on the employer's careers site by ApplyAll. We show every change we've seen including removals.
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