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For Companies At a Glance
- Tasks: Lead credit risk analytics, optimise pricing, and drive data-driven decisions for product performance.
- Company: Join a dynamic fintech company focused on innovation and growth.
- Benefits: Competitive salary, flexible working options, and opportunities for professional development.
- Why this job: Make a real impact by shaping credit strategies and enhancing product offerings.
- Qualifications: Experience in decision science, credit risk analytics, and strong leadership skills required.
- Other info: Fast-paced environment with excellent career advancement opportunities.
The predicted salary is between 43200 - 72000 £ per year.
As a Credit Risk Analytics Lead you will lead on decision science, credit models, portfolio performance and pricing, and play a key role in driving fundamental improvements in our credit and product performance, policy and strategy. You will be a senior member of the team responsible for producing tangible insights to the business which will not only monitor and control risk, but also help scale and grow our products through data driven decisions. This makes you the go-to person when the business requires insights on customer behaviour and any key performance metrics which include profitability, credit risk performance and operational performance metrics. This role also has responsibility for setting and optimising product pricing, that is market competitive while providing the coverage and margins required to deliver value to Kriya.
What You’ll Do
- Work closely with our risk leadership team to provide insights to optimise our underwriting and credit decisioning processes.
- Leverage latest data science, machine learning and artificial intelligence to build systematic risk models for our credit products.
- Produce portfolio monitoring and investigative analysis to explain trends and answer questions from key stakeholders; making recommendations on how to enhance our products and processes.
- Develop and optimise our pricing models using financial modelling techniques.
- Produce portfolio management information for both internal and external stakeholders and present insight and findings in a clear non-technical way that is easy for stakeholders to digest and understand.
- Conduct rigorous impact analysis on credit strategies, reassessing and optimising how we make credit decisions.
- Support the collections and recovery team with data driven insight and collections strategies.
- Collaborate with other teams in developing our predictive models, product features and processes.
Requirements
- Proven experience in decision science, credit risk analytics, data modelling and AI, ideally within financial services or fintech.
- Strong understanding of risk disciplines including unit profitability evaluation, pricing, risk appetite setting, and credit policy design.
- Experience with B2B/SME lending is highly desirable, though not essential.
- Demonstrated ability to influence and collaborate with cross-functional teams and senior stakeholders.
- Strong leadership and people management skills with a track record of building high-performing teams.
- Exceptional analytical and problem-solving abilities with a hands-on approach.
- Excellent communication skills, particularly in translating complex findings into accessible, actionable insights.
- Organised, proactive, and able to manage multiple priorities across different products and development stages.
- Comfortable working in a fast-paced, evolving environment with a start-up / build-it-yourself mindset.
Credit Risk Analytics Lead in London employer: Kriya
Contact Detail:
Kriya Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Credit Risk Analytics Lead in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend events, and connect on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Prepare for interviews by practising common questions and scenarios related to credit risk analytics. We recommend doing mock interviews with friends or using online platforms to get comfortable with your responses.
✨Tip Number 3
Showcase your skills through projects or case studies. If you’ve worked on relevant data models or analyses, be ready to discuss them in detail. This will demonstrate your hands-on experience and problem-solving abilities.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Credit Risk Analytics Lead in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the role of Credit Risk Analytics Lead. Highlight your experience in decision science and credit risk analytics, and don’t forget to showcase any relevant projects that demonstrate your ability to drive improvements in credit performance.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re the perfect fit for this role. Mention specific examples of how you've used data-driven insights to influence decision-making and improve product performance in the past.
Showcase Your Analytical Skills: Since this role is all about analytics, make sure to include examples of your analytical prowess. Talk about the tools and techniques you’ve used, like machine learning or financial modelling, and how they’ve helped you achieve results in previous roles.
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates from our team!
How to prepare for a job interview at Kriya
✨Know Your Numbers
As a Credit Risk Analytics Lead, you'll need to be comfortable with data. Brush up on key metrics related to credit risk performance and profitability. Be ready to discuss how you've used data to drive decisions in the past.
✨Showcase Your Leadership Skills
This role requires strong leadership and collaboration. Prepare examples of how you've led teams or influenced stakeholders in previous roles. Highlight your ability to build high-performing teams and manage cross-functional projects.
✨Simplify the Complex
You'll need to present complex findings in an accessible way. Practice explaining your analytical insights in simple terms. Think about how you can make your past experiences relatable to non-technical stakeholders.
✨Stay Current with Trends
Familiarise yourself with the latest trends in decision science, machine learning, and AI as they relate to credit risk. Be prepared to discuss how these technologies can enhance credit models and improve product performance.
