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- Tasks: Build and deploy innovative AI products using LLMs and GenAI technologies.
- Company: Leading consumer-focused organisation in health and insurance, prioritising data and AI.
- Benefits: Competitive salary, flexible working, and strong career growth opportunities.
- Other info: Work closely with senior stakeholders and enjoy high visibility across the business.
- Why this job: Make a real impact with cutting-edge AI solutions in a collaborative environment.
- Qualifications: 5+ years in data science, strong Python skills, and experience with LLMs.
The predicted salary is between 70000 - 90000 £ per year.
Are you a Senior Data Scientist who's moved beyond traditional modelling into LLMs, GenAI, and production AI systems? I'm hiring for a Senior Data Scientist to join a high-impact AI team within a leading consumer-focused organisation. This is a hands-on, end-to-end AI role working on large, complex, unstructured problems - building real products, not proof-of-concepts.
A well-established organisation in the consumer health / insurance space, offering products that combine financial services with incentives for healthier living (including subscription-led rewards models). Data and AI are central to how the business operates, with strong investment and leadership visibility - giving this team real ownership over innovative, business-critical solutions.
You'll sit within a specialist AI team, working alongside both classical data scientists and AI engineers. This team focuses on:
- LLMs, GenAI, and agentic workflows
- Solving unstructured, complex problems
- Building AI products used across underwriting, claims, customer experience, and more
Expect to work on 1-2 major projects, with high-impact, end-to-end ownership.
What you'll be doing:
- Build and deploy LLM-based applications, including RAG systems, chatbots, and agentic workflows
- Apply traditional ML techniques (e.g. regression, classification, gradient boosting) where appropriate
- Design and deliver end-to-end AI systems from discovery to production
- Develop agentic workflows across areas like underwriting and claims
- Work closely with business stakeholders to define requirements and shape solutions
- Deploy models using modern MLOps practices (APIs, microservices, CI/CD, containers)
- Collaborate with engineers, product teams, and senior stakeholders across the business
Tech stack:
- Python & SQL (essential)
- GCP (preferred, but flexible depending on experience)
- LLMs / GenAI / RAG / agentic frameworks (LangChain, LlamaIndex etc.)
- MLOps tools: Git, CI/CD, Docker, Kubernetes, APIs
Core requirements:
- ~5+ years in data science / machine learning
- Strong foundation in traditional ML (e.g. XGBoost, regression, statistical modelling)
- Hands-on experience with LLMs / GenAI / NLP / AI systems
- Experience deploying models into production (not just experimentation)
- Familiarity with MLOps, CI/CD, and containerisation
- Strong stakeholder skills - comfortable working with department heads and leading projects
Nice to have:
- Experience in regulated industries (insurance, finance, etc.)
- Customer-focused product experience
- Strong academic background in a quantitative field
- Exposure to building agentic workflows or RAG systems in production
Why this role:
- Work on real AI products, not just experimentation
- End-to-end ownership across modelling, deployment, and impact
- Exposure to cutting-edge GenAI and agentic systems
- Highly collaborative, cross-functional environment
- Strong visibility across the business
Interview process:
- ~30-minute culture fit interview
- ~Technical interview (solution design + deployment / ML discussion)
- ~Final interview with senior leadership (CDO)
Working style:
- ~2 days per week in London (flexible for Midlands candidates)
- Ideally Tues/Weds in office
- Cross-functional, collaborative environment with strong stakeholder interaction
Senior Data Scientist (Python) in London employer: Harnham - Data & Analytics Recruitment
Contact Detail:
Harnham - Data & Analytics Recruitment Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist (Python) in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, attend meetups, and engage with online communities. We all know that sometimes it's not just what you know, but who you know that can help you land that Senior Data Scientist role.
✨Tip Number 2
Prepare for those interviews! Brush up on your technical skills, especially around LLMs and MLOps. We recommend doing mock interviews with friends or using platforms that simulate real interview scenarios to get comfortable with the process.
✨Tip Number 3
Showcase your projects! Whether it’s through a portfolio or GitHub, let your work speak for itself. We want to see how you've tackled complex problems and built AI products, so make sure to highlight your hands-on experience.
✨Tip Number 4
Apply directly through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who take the initiative to connect with us directly.
We think you need these skills to ace Senior Data Scientist (Python) in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the Senior Data Scientist role. Highlight your hands-on experience with LLMs, GenAI, and any production AI systems you've worked on. We want to see how you’ve tackled complex problems in the past!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and how your background aligns with our mission at StudySmarter. Don’t forget to mention specific projects or achievements that demonstrate your expertise.
Showcase Your Technical Skills: Since this role requires strong Python and SQL skills, make sure to highlight relevant projects where you’ve used these technologies. If you’ve deployed models using MLOps practices, let us know! We love seeing practical applications of your skills.
Apply Through Our Website: We encourage you to apply directly through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and ensure it reaches the right people. We can’t wait to see what you bring to the table!
How to prepare for a job interview at Harnham - Data & Analytics Recruitment
✨Know Your Tech Stack Inside Out
Make sure you’re well-versed in Python, SQL, and the specific tools mentioned in the job description like GCP, Docker, and Kubernetes. Brush up on your knowledge of LLMs and GenAI, as you'll likely be asked to discuss how you've applied these technologies in real-world scenarios.
✨Showcase Your End-to-End Experience
Prepare to discuss your experience with building and deploying AI systems from start to finish. Be ready to share specific examples of projects where you’ve taken ownership, especially those involving complex, unstructured problems. Highlight your role in collaborating with stakeholders to shape solutions.
✨Demonstrate Your Stakeholder Skills
Since this role involves working closely with business stakeholders, practice articulating how you’ve effectively communicated technical concepts to non-technical audiences. Think of examples where you’ve led projects or influenced decision-making within a team.
✨Prepare for Technical Challenges
Expect to face technical questions that test your understanding of traditional ML techniques and MLOps practices. Brush up on regression, classification, and model deployment strategies. Consider preparing a mini-case study to demonstrate your problem-solving approach during the technical interview.