Senior Data Scientist in Manchester

Finova is the UK’s largest financial services technology provider, supporting one in every five mortgages nationwide. Our agile, cloud-native solutions enable over 60 banks, building societies, specialist lenders, equity release providers and a network of 2,400+ brokers to stay ahead in a competitive market. Built on open architecture and backed by deep industry expertise, our platform is designed to scale. Each year, we process over £50 billion in loans, manage nearly £50 billion in savings, and support the digital servicing of more than 650,000 UK borrower accounts. Be part of a team that’s driving innovation, enabling growth and shaping the future of UK lending.

We’re hiring a Senior Data Scientist to help build our next-generation, explainable credit decisioning capability for mortgage lenders. This is a foundational, hands‑on role where you will design and deliver our first production‑grade credit triage and decision support models built on real historical mortgage data and engineered for transparency, defensibility, and lender‑grade governance. You’ll work at the intersection of credit risk, applied machine learning, and regulated SaaS delivery. Your work will directly shape how lenders make faster, more consistent underwriting decisions, and how our platform scales into a trusted, compliant credit technology solution.

You will balance statistical rigour with pragmatic delivery, ensuring we ship value quickly while maintaining the stability, fairness, and explainability expected in lender environments. You will collaborate closely with Underwriting and Risk SMEs, Data Engineering, Platform Engineering, and Product to design models that are interpretable, auditable, and suitable for real‑time production use. This is not a research role, it’s a product‑focused, impact‑driven modelling role at the heart of our credit decisioning strategy.

What Will You Be Doing?

• Analysing historical mortgage data, rationalising inconsistent data schemas, and performing inference on referred or rejected applications
• Translating underwriting policies and lender risk appetite into measurable features and well‑defined modelling datasets
• Designing interpretable models such as logistic regression or constrained gradient boosting, prioritising lender‑grade explainability and stability
• Evaluating models using credit‑specific metrics including AUC, Gini, calibration, PSI, fairness indicators, and stability measures across key borrower segments
• Identifying and mitigating selection bias, data drift, and other modelling risks
• Ensuring full reproducibility across data snapshots, code, and model artefacts
• Collaborating with engineers to ensure training features (Python/Pandas) can be reproduced with zero skew in production (SQL/API)
• Working with Platform Engineering to deploy models using cloud‑native ML infrastructure
• Establishing monitoring for model degradation, drift, fairness, and operational reliability
• Designing cost aware, scalable solutions appropriate for multi‑tenant lender deployments
• Maintaining a pragmatic, outcome driven mindset, shipping simple, defensible models first, before fine tuning

About You:

• You’re a hands‑on Data Scientist with strong experience in modelling, ideally within mortgages or consumer lending
• You balance statistical rigour with practical delivery, favouring simple, interpretable models that deliver value quickly
• You have strong proficiency in Python and modern ML tooling (scikit learn, XGBoost/LightGBM, Pandas) and are comfortable working directly with engineers to ship models into production
• You understand the realities of regulated environments and the importance of governance, validation, calibration, monitoring, and fairness
• You’re skilled at working with structured financial datasets, including rationalising inconsistent schemas and engineering defensible features
• You communicate modelling trade‑offs clearly — including interpretability vs lift, complexity vs speed, and robustness vs delivery pace
• You produce clear, audit‑ready documentation and value transparency, defensibility, and explainability
• You prefer to ship simple, robust solutions early and iterate rather than pursuing perfection at the expense of impact
• You bring a modern mindset comfortable with APIs, cloud‑native ML tools, and production constraints
• You’re curious, pragmatic, and motivated by the real‑world impact of your work

What We Offer:

• Hybrid working: We operate a hybrid working model, with most teams spending around three days a week in the office and with our customers.
• Holiday: 25 days holiday plus bank holidays, bank holiday trading and holiday purchase options, the opportunity to work from anywhere in the world for up to 4 weeks per year.
• Looking After You: Life Assurance, Group Income Protection, Private Medical Insurance, a pension scheme via Salary Exchange, an Employee Assistance Programme, and access to a Virtual GP.
• Family‑Friendly Policies: Enhanced maternity and paternity pay, as well as paid time off for fertility treatments and pregnancy loss.
• Extra Perks: Cycle to Work Scheme, discounts on shops, restaurants, and gym memberships, free fresh fruit daily, and opportunities to join colleague networks and social groups.
• Giving Back: One paid volunteering day annually and the Give‑As‑You‑Earn scheme to support your favourite charities.

Equal Opportunity Statement: We value diversity and are committed to creating an inclusive environment for all employees. If you’re passionate about this role but don’t meet all the criteria, please reach out—we’d love to discuss how your skills and experiences align with our needs.