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- Tasks: Lead a dynamic Data Science team and drive impactful machine learning solutions.
- Company: Fast-growing UK FinTech business with a focus on data innovation.
- Benefits: Hybrid working, competitive pension, extra paid leave, and employee support programmes.
- Why this job: Make a real difference in the financial sector with cutting-edge technology.
- Qualifications: Proven ML experience, strong Python and SQL skills, and leadership capabilities.
- Other info: Collaborative office environment with excellent career growth opportunities.
My client is a fast-growing UK FinTech business serving thousands of customers. They are investing heavily in their data capability and are now looking to appoint a Lead Data Scientist to drive end-to-end machine learning delivery within a regulated financial environment. This is a hands-on leadership role combining technical ownership, team development, and production-grade model deployment.
The Role
- Lead and develop a growing Data Science team, setting standards and delivery cadence
- Own end-to-end ML solutions - from problem framing and feature engineering to deployment, monitoring, and governance
- Translate business objectives into modelling strategies aligned to risk appetite and operational constraints
- Build and deploy models using Python, SQL, and AWS (SageMaker or equivalent)
- Partner closely with Engineering, Data, and Risk/Financial Crime teams to ensure robust, production-ready solutions
- Establish monitoring frameworks for performance, drift, and retraining
- Drive clear documentation, traceability, and governance appropriate for a regulated environment
This role requires someone who thinks beyond experimentation - focusing on operational impact, adoption, and long-term model performance.
Essential Experience
- Proven commercial ML/Data Science delivery with measurable impact
- Experience taking models into production and managing performance over time
- Prior experience leading or mentoring Data Scientists
- Strong Python (pandas, numpy, scikit-learn or similar)
- Strong SQL (complex joins, aggregations, analytical functions)
- Solid grounding in applied statistics, evaluation design, calibration, bias/fairness
- Experience working closely with Engineering/Data teams in production-first environments
- Comfortable operating within regulated industries
Desirable
- AWS experience (S3, Athena/Glue, IAM, Lambda)
- SageMaker or equivalent ML platform experience
- Financial services domain knowledge (risk, fraud, affordability, payments)
- Experience with model explainability and governance documentation
Package & Benefits
- Hybrid working model
- Competitive pension
- Additional paid leave (birthday, charity, wellbeing, life events)
- Employee assistance programme & Virtual GP
- Modern collaborative office environment
Interested? Please Click Apply Now!
Lead Data Scientist in Manchester employer: Adria Solutions
Contact Detail:
Adria Solutions Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Data Scientist in Manchester
✨Tip Number 1
Network like a pro! Reach out to your connections in the FinTech space and let them know you're on the lookout for a Lead Data Scientist role. A personal recommendation can go a long way in getting your foot in the door.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your end-to-end machine learning projects. Highlight your experience with Python, SQL, and AWS, and make sure to include any impactful results you've achieved.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and leadership skills. Be ready to discuss how you've led teams and delivered ML solutions in regulated environments, as this will be key for the role.
✨Tip Number 4
Don't forget to apply through our website! We want to see your application and help you land that dream job. Plus, it shows you're serious about joining our team!
We think you need these skills to ace Lead Data Scientist in Manchester
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the Lead Data Scientist role. Highlight your experience with machine learning, Python, and SQL, and don’t forget to mention any leadership roles you've had!
Craft a Compelling Cover Letter: Use your cover letter to tell us why you’re the perfect fit for this position. Share specific examples of how you've driven ML solutions in the past and how you can contribute to our team’s success.
Showcase Your Technical Skills: Since this role is hands-on, make sure to detail your technical expertise in Python, SQL, and AWS. We want to see how you've applied these skills in real-world scenarios, especially in regulated environments.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role without any hiccups!
How to prepare for a job interview at Adria Solutions
✨Know Your ML Inside Out
Make sure you brush up on your machine learning concepts and techniques. Be ready to discuss your experience with end-to-end ML solutions, from problem framing to deployment. They’ll want to see how you can translate business objectives into effective modelling strategies.
✨Showcase Your Leadership Skills
As a Lead Data Scientist, you'll be expected to lead and develop a team. Prepare examples of how you've mentored or guided other Data Scientists in the past. Highlight your ability to set standards and ensure delivery cadence within a team.
✨Demonstrate Technical Proficiency
Be prepared to dive deep into your technical skills, especially in Python and SQL. They’ll likely ask about your experience with libraries like pandas and scikit-learn, as well as your familiarity with AWS services like SageMaker. Have specific projects in mind that showcase your expertise.
✨Understand the Regulatory Landscape
Since this role is within a regulated financial environment, it’s crucial to understand compliance and governance. Brush up on how you’ve established monitoring frameworks for model performance and drift, and be ready to discuss your approach to documentation and traceability.