Data Science Engineer
- Rate: £570 per day (Umbrella)
- Duration: 6 months (maternity cover)
- Location: Reading or Shoreditch
- Hybrid: 2-3 days onsite initially (first 1-2 months), Greater flexibility thereafter
- Working pattern: Full time, 9-5, collaboration with US West Coast teams & occasional meetings after 5pm (flexible start the following day)
A global technology organisation is seeking a Data Science Engineer to join its commercial analytics team on a 6-month maternity cover contract.
This role sits at the intersection of data science and data engineering, focusing on building predictive models that identify revenue opportunities while also developing the underlying data pipelines that support them.
You'll work closely with commercial stakeholders across the US West Coast, helping turn complex customer and sales data into actionable insights that support sales strategy and growth initiatives.
Key Responsibilities
- Build and maintain propensity and predictive models to identify revenue growth opportunities within the customer base
- Analyse large commercial datasets to identify patterns, performance gaps and opportunities
- Develop and maintain data pipelines that support model development and data workflows
- Evaluate and improve the performance of predictive models and identify areas for optimisation
- Work autonomously to design, test and implement scalable data science solutions
- Collaborate with data engineering teams to productionise models and ensure data reliability
- Translate analytical findings into insights that support sales and commercial decision making
- Engage with global stakeholders, including teams based in the US West Coast
Key Requirements
- 5+ years' experience in data science, machine learning, or analytics engineering roles
- Strong SQL expertise (core requirement) for querying and manipulating large datasets
- Strong Python experience for machine learning and modelling
- Proven experience building predictive or propensity models
- Experience developing data pipelines or working closely with data engineering workflows
- Ability to work autonomously in a fast-paced environment
- Experience with Databricks highly desirable
- Experience presenting insights to non-technical stakeholders is beneficial
