At a Glance
- Tasks: Transform large datasets into predictive models and support data-driven solutions.
- Company: Dynamic financial services firm with a focus on innovation.
- Benefits: Hybrid working, competitive salary, and opportunities for professional growth.
- Other info: Join a high-impact team with excellent career advancement opportunities.
- Why this job: Lead impactful projects in a regulated environment and shape the future of data analytics.
- Qualifications: Strong Python, SQL skills, and experience in credit risk modelling.
The predicted salary is between 80000 - 100000 £ per year.
We are seeking an experienced Lead Data Scientist to join a high-impact team developing predictive analytics and data products within a regulated financial services environment.
Location - London
Contract – Inside IR35
Working Pattern - Hybrid
Skills & Experience
This role will focus on transforming large-scale customer datasets into robust, auditable predictive models, supporting forecasting, risk analysis and commercial data products.
- Strong Python (Pandas, NumPy, Scikit-learn) and SQL skills.
- Experience with Snowflake or similar cloud data platforms.
- Proven track record building predictive models in regulated financial services environments.
- Credit risk modelling experience, including PD models, scorecards or similar.
- Strong understanding of model governance, validation and audit requirements.
- Experience with GDPR and AI governance frameworks.
Key responsibilities
- Build and deploy predictive and credit risk models.
- Lead exploratory data analysis, feature engineering, model validation and monitoring.
- Develop forecasting, simulation and stress-testing models.
- Work with data engineering teams to create modelling-ready datasets using Snowflake.
- Ensure models and processes meet regulatory and governance standards.
- Collaborate closely with product and business stakeholders to deliver data-driven solutions.
Due to the volume of applications received for positions, it will not be possible to respond to all applications and only applicants who are considered suitable for interview will be contacted.
Proactive Appointments Limited operates as an employment agency and employment business and is an equal opportunities organisation.
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Lead Data Scientist in London employer: Proactive Appointments
As a Lead Data Scientist at our London-based firm, you will be part of a dynamic and innovative team dedicated to developing cutting-edge predictive analytics within the financial services sector. We pride ourselves on fostering a collaborative work culture that encourages professional growth and offers opportunities to work with advanced technologies like Snowflake, ensuring you stay at the forefront of data science. Our hybrid working model provides flexibility, while our commitment to regulatory excellence ensures that your contributions will have a meaningful impact in a highly respected environment.
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We think you need these skills to ace Lead Data Scientist in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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✨Brush Up on Your Statistics
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
