Data Scientist
Job description
Data Scientist |
Berkshire · Hybrid · Financial Services · Salary DOE + benefits
This is a chance to join a data team at exactly the right point in its journey.
The platform is built. The Data Engineering and Analytics teams are established. The foundations are there.
Now they’re looking for a Data Scientist to help take Data Science to the next level.
You won’t be joining a team where models sit in notebooks. You’ll have the opportunity to build, deploy and influence how modelling is used across customer behaviour, risk and operational efficiency.
What you’ll be doing
- Turn real business problems into production-ready models
- Build and validate models using Python
- Apply statistics, experimentation and A/B testing
- Work with Engineering on data, features and productionisation
- Bring more advanced modelling into the wider Analytics function
- Influence how Data Science is applied across the business
- Present your findings to senior stakeholders and turn complex analysis into clear business decisions
- 2–3+ years’ commercial Data Science experience
- Strong statistical and machine learning foundations
- Excellent Python, pandas, NumPy and scikit-learn
- Experience getting models into production
- Understanding of MLOps, CI/CD and deployment
- Someone who values practical, explainable modelling over complexity for complexity’s sake
- Strong communication skills
Financial Services or fintech experience, Microsoft Fabric, Azure ML, Databricks, MLflow, DVC or Git.
Why
You’re not walking into a blank canvas.
You’re joining an established data function with the platform, engineering capability and analytical foundations already in place, with genuine scope to help shape what Data Science looks like across the business.
If you’re a Data Scientist looking for a role where you can build, influence and see your models actually used, get in touch.
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Interested in this role?