Senior data scientist
| Company: | Hays Specialist Recruitment |
|---|---|
| Salary: | £550 to £700 a year |
| Hours: | Full-time |
| Location: | Manchester, M2 2BY |
| Job type: | Contract |
| Posting date: | 25 Aug 2026 |
| Closing date: | 15 Sept 2026 |
Summary
Senior Data Scientist - Contract Role, Manchester City Centre
Role Title: Senior Data Scientist (Contract)Contract Type: Inside IR35, initial 6-month term, strong likelihood of extension
Day Rate: £650 per day
About the Business
We're partnering with a fast scaling technology business in the North of England that's investing heavily in data driven product development. This is a hands on, individual contributor focused role for a Senior Data Scientist who wants to own technical delivery on high impact projects, without the overhead of formal line management.
About the RoleThis role is for someone who thrives on solving ambiguous, high value problems independently, taking a business question, shaping it into a data science approach, and owning it from start to finish through to production. You'll work closely with a small team of data scientists and engineers, contributing technical depth and mentoring more junior colleagues along the way, but the core of the role is hands on delivery.
Key Responsibilities
- Model ownership from start to finish: Design, build, and deploy production grade machine learning models, from problem framing and experimentation through to live deployment and monitoring.
- Technical depth: Apply strong statistical modelling, ML, and (where relevant) NLP/LLM techniques to solve real business problems, not just exploratory analysis.
- Experimentation and measurement: Design and run experiments (A/B testing, causal inference) to validate impact and guide decision making.
- Cross-functional delivery: Partner closely with Product, Engineering, and MLOps teams to move ideas from prototype into scalable production systems.
- Mentorship: Support and coach junior data scientists on technical approach, code quality, and best practice, without formal management responsibility.
- Stakeholder communication: Translate complex technical findings into clear, actionable insights for non-technical stakeholders.
- Best practice: Contribute to how the wider data science function approaches tooling, methodology, and model governance.
Technical Environment
- Languages/Tools: Python (NumPy, Pandas, Scikit learn), deep learning frameworks (PyTorch/TensorFlow), SQL.
- MLOps: MLflow, cloud ML platforms (Azure ML, AWS SageMaker, or Databricks).
- Focus areas: Predictive modelling, recommender systems/personalisation, and increasingly, applied LLM/GenAI use cases, reflecting where the market is heading right now.
- Infrastructure: Cloud based (AWS/GCP/Azure, client dependent).
What We're Looking For
- Strong commercial experience as a data scientist, with a proven track record of shipping models into production, not just notebook-based analysis.
- Expert level Python and solid grounding in statistics/experimental design.
- Experience with recommender systems, personalisation, or ranking techniques is highly desirable.
- Exposure to LLMs, Generative AI, or conversational AI products is a strong plus given current market demand.
- Comfortable taking an unclear business problem and shaping it into a scoped data science approach, including recognising where ML isn't the right answer.
- Strong communication skills, able to flex between technical depth and clear business-facing summaries.
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