Credit Risk Analytics Lead

LGBT Great; Greater London; On-site; GBP 80,000 - GBP 100,000; Full time

Job summary

A financial services company in Greater London is seeking a Credit Risk Analytics Lead. This role involves leading decision science, credit models, and portfolio performance. You will produce insights driving improvements in credit and product strategies, collaborating with teams to enhance decision-making processes. The ideal candidate has proven expertise in analytics and data modeling within financial sectors. The position demands strong leadership, problem-solving skills, and a proactive mindset in a fast-paced environment.

Qualifications

• Proven experience in decision science and credit risk analytics.
• Strong understanding of risk disciplines and credit policy design.
• Demonstrated ability to influence cross-functional teams.

Responsibilities

• Lead insights to optimise underwriting and credit decisioning.
• Produce portfolio monitoring analysis and recommendations.
• Support collections strategies with data-driven insights.

Skills

Decision science

Credit risk analytics

Data modelling

AI

Analytical skills

Communication skills

Job description

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

Qualifications

• 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.