Principal Analyst

At Hometrack we are redefining the mortgage journey for lenders, brokers, and consumers by providing market-leading digital valuation, property risk decisioning, and property data services. Our key commercial segments include financial services—particularly mortgage lenders, including nine of the top ten UK providers—as well as property developers and investors.

Hometrack is seeking maternity cover for a senior analytics leader to own and lead Property Risk Analytics across our product suite. This role is suitable for a Principal Analyst, Senior Consultant, or existing Head of Analytics with strong technical capability, great communication skills, and experience in mortgage lending.

This role has a strong hands-on component and is focused on ensuring the quality, performance, and commercial impact of Hometrack’s Property Risk data products. You will lead complex analytical work on mortgage application and survey data, back-test and evolve property risk metrics, and deliver bespoke lender analysis to support both existing clients and new product growth.

You will work closely with engineering, product, analytics, and customers to ensure property risk products are robust, explainable, and aligned to real lender decision-making and risk frameworks.

• Lead the improvement, maintenance, and performance monitoring of Hometrack’s Property Risk data products and metrics.
• Design and deliver back-testing and performance analysis of property risk indicators using mortgage application, valuation, and survey datasets.
• Identify data quality issues, coverage gaps, and model limitations, and work with the engineering and analytics teams to resolve them.
• Translate analytical findings into clear, actionable recommendations for product evolution.
  

• Deliver bespoke lender analysis to support client decision-making, product adoption, and commercial conversations.
• Support the commercial success of new Property Risk products, providing analytics that demonstrate value, risk reduction, or operational efficiency for lenders.
• Act as a senior analytical point of contact for key clients, helping them understand how property risk outputs should be interpreted and embedded into their processes.
• Support go-to-market activity with robust, evidence-based insight.
• Feed real-world client challenges and lender policy requirements back into product and analytics roadmaps.
  

• Work closely with engineering to ensure analytical requirements are translated into scalable, production-ready data products.
• Collaborate with Data Science to improve risk product capability.
• Partner with other analysts to deliver product insight, client reporting, and deep-dive investigations.
  

• Engage confidently with stakeholders at all levels, from technical teams to senior client and commercial leadership.
• Explain complex analytical concepts, risk metrics, and data limitations in a clear and pragmatic way.
• Act as an internal advocate for strong analytical standards, explainability, and data driven decision making.
  

• Strong background in data analytics within a mortgage lender, property business, consultancy, or a software/data supplier to mortgage lenders.
• Proven experience conducting complex analysis on large datasets, including performance analysis and back-testing of risk metrics.
• Strong programming and data analysis capability (e.g. SQL, Python, Spark, or similar), with the ability to turn analysis into clear insight.
• Experience working closely with engineering teams to develop and maintain data products.
• Confident communicator, able to engage credibly with clients and internal stakeholders.

• Understanding of mortgage lending processes, property valuation and survey data, and/or property or secured credit risk.
• Experience working with mortgage application data, surveyor reports, or valuation data.
• Familiarity with cloud-based analytics environments (AWS or Azure).
• Experience using Databricks or similar analytics platforms.
• Background in analytics supporting product development or go-to-market activity.
  

• Bachelor’s degree in a quantitative field such as Mathematics, Economics, Physics, Computer Science, or similar.
• Advanced degree or equivalent professional experience is advantageous.

Strong applied statistical knowledge, with experience using statistical techniques in real-world analytical problems.

• Everyday Flex – greater flexibility over where and when you work
• 25 days annual leave + additional days for long service
• Day off for your house move, good deed day, and digital detox day
• Cycle to Work and Electric Car schemes
• Free Calm App membership
• Enhanced parental leave
• Fertility treatment financial support
• Group income protection and private medical insurance
• On-site gym in London 
• 7.5% employer pension contribution
• Discretionary annual bonus up to 10%
• Talent referral bonus up to £5,000