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For Companies At a Glance
- Tasks: Lead a data science team to innovate credit, fraud, and pricing models.
- Company: Fast-growing fintech at the forefront of AI and analytics.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Why this job: Make a real impact in AI adoption and shape the future of finance.
- Qualifications: Strong background in financial services and expertise in Python, SQL, and ML.
- Other info: Join a dynamic team and influence senior stakeholders with your insights.
The predicted salary is between 48000 - 72000 £ per year.
Job Description
Lead Data Scientist – Credit Risk/Pricing
A fast-growing fintech is searching for a Lead Data Scientist to spearhead their next phase of AI and analytics innovation. You’ll combine hands-on modelling with leadership responsibilities, guiding a small team while shaping the company’s long-term data science strategy.
This role will put you at the centre of credit, fraud, and pricing model innovation, while giving you the autonomy to drive AI adoption across the business. If you enjoy bridging technical depth with commercial influence, this is a chance to make a real mark.
Required Background
- Strong background in financial services, consumer lending, or fintech.
- Expert in credit, fraud and pricing modelling.
- Advanced skills in Python, SQL, and ML frameworks.
- Proven ability to design, deploy, and monitor models in production.
- Leadership experience – mentoring or managing data science teams.
- Confidence in regulated environments: model governance, monitoring.
- Excellent communicator who can influence senior stakeholders.
The Opportunity
- Lead and develop a small data science team.
- Build and enhance credit risk, fraud, and pricing models.
- Explore and implement advanced ML techniques.
- Translate complex analytics into clear recommendations for senior leadership.
- Act as the organisation’s AI/ML thought leader, keeping ahead of emerging trends.
Lead Data Scientist - Credit Risk/Pricing employer: Kinarden Search
Contact Detail:
Kinarden Search Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Data Scientist - Credit Risk/Pricing
✨Tip Number 1
Network like a pro! Reach out to connections in the fintech space, especially those who work with credit risk or data science. A friendly chat can lead to insider info about job openings that aren't even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your best projects in credit, fraud, and pricing modelling. This will not only impress potential employers but also give you something tangible to discuss during interviews.
✨Tip Number 3
Prepare for the interview by brushing up on your leadership stories. Be ready to share how you've mentored teams and influenced stakeholders. We want to hear how you can bridge the gap between technical depth and commercial impact!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Lead Data Scientist - Credit Risk/Pricing
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Lead Data Scientist role. Highlight your experience in financial services and your expertise in credit, fraud, and pricing modelling. We want to see how your skills align with what we're looking for!
Showcase Your Projects: Include specific projects where you've designed, deployed, or monitored models in production. We love seeing real examples of your work, especially if they demonstrate your leadership skills and technical prowess in Python and SQL.
Communicate Clearly: Since this role involves influencing senior stakeholders, make sure your application reflects your communication skills. Use clear, concise language to explain complex analytics and how they can drive business decisions. We appreciate clarity!
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. Plus, it shows you're keen on joining our team at StudySmarter!
How to prepare for a job interview at Kinarden Search
✨Know Your Models Inside Out
Make sure you can discuss your experience with credit, fraud, and pricing models in detail. Be prepared to explain the methodologies you've used, the challenges you faced, and how you overcame them. This will show your technical depth and understanding of the field.
✨Showcase Your Leadership Skills
Since this role involves leading a small team, be ready to share examples of your leadership experience. Talk about how you've mentored others, managed projects, or influenced decisions. Highlighting your ability to guide a team will resonate well with the interviewers.
✨Communicate Clearly and Confidently
As an excellent communicator, you need to convey complex analytics in a way that senior stakeholders can understand. Practice explaining your past projects and their impact on the business in simple terms. This will demonstrate your ability to bridge the gap between technical and commercial aspects.
✨Stay Ahead of Trends
Research the latest trends in AI and machine learning, especially as they relate to credit risk and pricing. Being able to discuss emerging technologies and how they could benefit the company will position you as a thought leader and show your passion for the field.
