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- Tasks: Lead the design and development of credit risk models from scratch.
- Company: Join a dynamic fintech startup backed by experienced investors and a strong founding team.
- Benefits: Enjoy a competitive salary, company pension scheme, and private medical care.
- Why this job: This role offers autonomy, technical challenges, and visibility across the business.
- Qualifications: Experience in developing credit risk scorecards and proficiency in Python required.
- Other info: This is a remote position within the UK, perfect for self-starters.
The predicted salary is between 70000 - 100000 £ per year.
Up to £80,000 + bonus
We’re hiring a Senior Data Scientist to help shape the next generation of machine-learning-powered products within a commercially focused, data-driven organisation that has undergone a major data transformation in recent years.
This is a high-impact role where you’ll work across the full data science lifecycle — from deep-dive analysis and model development to deploying scalable ML solutions that directly influence strategic and operational decisions.
What you’ll be doing
- Build, evaluate and deploy machine learning models to predict and classify customer behaviour
- Deliver insights across churn, retention, pricing, fraud, marketing and customer value
- Partner with commercial, product and regional teams to optimise business performance
- Conduct deep-dive analyses to uncover root causes of key business challenges
- Translate complex analysis into clear, actionable insights for senior stakeholders
- Contribute to dashboards and self-serve analytics to drive data-led decision making
- Act as a subject-matter expert for data science across the business
What we’re looking for
- Strong experience with Python and SQL (model building, analysis, visualisation)
- Solid understanding of data science techniques and libraries (Pandas, scikit-learn, supervised & unsupervised models, tree-based models)
- Proven experience with customer analytics (e.g. churn, CLTV, segmentation) – required
- Hands-on experience deploying ML models into production
- Exposure to cloud platforms (Azure and/or Databricks) and MLOps practices
- Excellent communication skills with the ability to influence non-technical stakeholders
- Comfortable working in fast-paced, cross-functional environments
Nice to have
- Master’s degree in Computer Science, Data Science, Machine Learning or a related field
Why apply?
- Work on real, business-critical data science problems with measurable impact
- High visibility role with senior stakeholder exposure
- Strong data and AI maturity with room to influence direction and best practice
- Competitive salary, bonus and hybrid working
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Senior Data Scientist employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist
✨Tip Number 1
Familiarise yourself with the latest trends in credit risk modelling, especially focusing on scorecard development. Being able to discuss recent advancements or case studies during your conversations can really set you apart.
✨Tip Number 2
Network with professionals in the fintech space, particularly those involved in credit risk. Engaging in relevant online forums or attending industry webinars can help you make valuable connections that might lead to referrals.
✨Tip Number 3
Prepare to showcase your hands-on experience with Python and any specific modelling techniques you've used. Be ready to discuss how you've applied these skills in previous roles, as practical examples will resonate well with the hiring team.
✨Tip Number 4
Understand the regulatory landscape surrounding credit risk. Being able to articulate your knowledge of model governance and validation processes will demonstrate your readiness for this strategic role.
We think you need these skills to ace Senior Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in developing credit risk scorecards and your proficiency in Python. Use specific examples that demonstrate your statistical and analytical skills, as well as your ability to collaborate with cross-functional teams.
Craft a Compelling Cover Letter: Write a cover letter that showcases your understanding of the role and the company. Emphasise your experience with credit risk modelling and your ability to operate autonomously. Mention why you are excited about joining a fintech startup and how you can contribute to their growth.
Highlight Relevant Skills: In your application, clearly outline your skills related to regulatory requirements and model governance. This will show that you understand the complexities of the role and are prepared to take on the responsibilities involved.
Follow Application Instructions: Ensure you send your application through the specified ‘Apply’ link and address it to Rosie Walsh. Double-check that all documents are attached and formatted correctly before submitting to avoid any delays.
How to prepare for a job interview at Harnham
✨Showcase Your Technical Skills
As a Senior Data Scientist, you'll need to demonstrate your proficiency in Python and statistical analysis. Be prepared to discuss specific projects where you've developed credit risk scorecards and the techniques you used. Highlight any experience with machine learning models, as this could set you apart.
✨Understand Regulatory Requirements
Familiarise yourself with the regulatory landscape surrounding credit risk. Be ready to discuss how you've navigated model governance and validation in previous roles. This knowledge will show that you can handle the compliance aspects of the role effectively.
✨Emphasise Collaboration Skills
This role requires working closely with data engineering and product teams. Prepare examples of how you've successfully collaborated with cross-functional teams in the past. Highlight your ability to communicate complex data concepts to non-technical stakeholders.
✨Demonstrate Autonomy and Initiative
As the first hire in credit risk, you'll need to take ownership of your work. Share instances where you've operated independently in unstructured environments. Discuss how you identify problems and take the initiative to solve them, showcasing your self-starter attitude.
