Data Science Lead (Contract)Central Manchester – Hybrid Working
Outside IR35 - 3 Month Contract (Likely Extension)We are supporting a large UK-based digital organisation undergoing a significant data and AI transformation, with growing demand for advanced analytics across commercial and customer-focused teams. This is a contract opportunity within a fast-moving Data Science function, working in a modern cloud-based environment.
The role sits within a commercial analytics team focused on delivering measurable business impact through applied machine learning and production-grade data science.
Key Focus Areas (Must-Have Experience)We are specifically looking for someone who has:
- Led data science projects in a commercial or enterprise environment
- Built and deployed customer churn prediction models in a commercial environment
- Developed Next Best Action / recommendation systems to drive customer engagement and value
- Delivered customer segmentation models (e.g. clustering, behavioural segmentation, lifecycle modelling)
- Strong experience in time series analysis and forecasting (e.g. demand, revenue, customer behaviour trends)
- Worked end-to-end in production data science environments, not just proof-of-concept models
- Strong hands-on experience using Python as a primary programming language
- Experience working within Databricks (notebooks, pipelines, or ML workflows)
- A strong mathematical and statistical background, with confidence in applying theory to real commercial problems
Role OverviewYou will lead the development and delivery of data science products that generate measurable business value. Working closely with cross-functional teams, you will guide technical delivery from concept through to production, ensuring solutions are scalable, robust, and aligned to business and regulatory requirements. You will also support team capability development where required, contribute to a high-performance culture, and help position data science as a strategic internal consultancy function within an outside IR35 engagement.
Responsibilities- Lead the development of data science products from ideation to production deployment
- Apply statistical, mathematical, and machine learning techniques to solve real-world commercial problems
- Develop, validate, deploy, and monitor machine learning models in production environments
- Build and maintain end-to-end data science solutions using modern MLOps practices
- Use cloud-based platforms (notably Databricks) to develop scalable data products
- Translate complex analytical outputs into clear, business-focused insights
- Collaborate with technical and non-technical stakeholders across multiple functions
- Ensure compliance with governance, regulatory, and internal data standards
- Continuously improve model performance, robustness, and business impact
Technical Skills & Experience- Proven experience in applied Data Science / Machine Learning roles within a commercial environment
- Strong proficiency in Python and SQL
- Hands-on experience with Databricks in a production or enterprise setting
- Experience with ML pipelines, version control (Git), and CI/CD workflows
- Exposure to MLflow or similar model tracking/deployment tools
- Strong foundation in statistics, probability, linear algebra, and applied mathematics
- Experience delivering models such as:
- Churn prediction models
- Customer segmentation frameworks
- Next Best Action / propensity models
- Time series forecasting models
About You- MSc, PhD, or equivalent experience in a highly quantitative discipline (e.g. Mathematics, Statistics, Physics, Computer Science, Data Science)
- Strong project capability with a hands-on technical mindset
- Comfortable working in fast-moving, agile environments
- Able to communicate insights clearly to both technical and non-technical stakeholders
- Collaborative, proactive, and delivery-focused
Additional Information- Hybrid working with regular office presence in Central Manchester
- Strong focus on data-driven decision-making and AI-led transformation
- Inclusive, collaborative working environment with modern tooling and practices