3 дня назад
Senior Finance Data Scientist (Fintech)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Senior Finance Data Scientist (IFRS9/Portfolio Modelling): Building and maintaining IFRS9 Expected Credit Loss models and portfolio forecasting components for UK and US revolving credit books with an accent on PD/LGD/EAD modelling, macroeconomic overlays, and financial forecast integration. Focus on calibrating and monitoring production models, backtesting spend and cashflow forecasts, and delivering explainable inputs for Finance and Risk.
Location: Hybrid, working from the London (Moorgate) offices 3 days per week
Company
is a profitable fintech platform providing business credit cards, spend management, savings products, and financial tools for small businesses.
What you will do
- Build, calibrate, implement, and monitor IFRS9 Expected Credit Loss models covering PD, LGD, EAD, staging/SICR logic, and macroeconomic overlays.
- Run and improve month-end ECL production, including scenario runs, combined outputs, Snowflake checks, provisioning, and year-end submissions.
- Develop and maintain portfolio models covering customers, balances, funding, repayments, finance charges, and bad debt.
- Build and backtest spend, cashflow, cohort, and segment forecasting components using Python and dbt.
- Diagnose model drift, recalibrate assumptions and overlays, and provide reliable inputs for Finance forecasts.
- Collaborate with FP&A, Risk, and Data Science while improving monitoring, automation, documentation, and AI-assisted workflows.
Requirements
- 2–5+ years of experience building statistical or credit risk models in Python and shaping data with SQL.
- Experience with credit risk modelling, ideally IFRS9 ECL, PD/LGD/EAD, staging, and model monitoring.
- Commercial understanding of revolving credit economics, including utilisation, arrears, defaults, recoveries, and portfolio growth.
- Ability to work end-to-end from analysis and calibration through production runs and stakeholder-ready forecast inputs.
- Strong autonomy, judgement, proactivity, and an explainable, controlled approach to applying AI.
Nice to have
- Experience with Snowflake, dbt, Fivetran, JupyterLab, Omni, Kubernetes, or Azure.
- Experience integrating portfolio or behavioural models with FP&A or financial planning models.
- Familiarity with LightGBM or similar gradient-boosted models.
- Exposure to model change control, independent validation, ECL disclosure packs, or UK and US credit portfolios.
Culture & Benefits
- Private healthcare with dental and optical services, worldwide travel insurance, and reproductive and hormonal health support.
- 28 days of holiday plus bank holidays, enhanced parental leave, and a pension scheme with up to 7% matching.
- Annual learning and wellbeing budget, six free therapy sessions per year, and a four-week fully paid sabbatical after qualifying anniversaries.
- Dog-friendly London offices with free drinks and snacks, recreational facilities, and cycle-to-work and season-ticket loan schemes.
Hiring process
- Applications are generally answered within 3 working days, or up to 5 working days during busy periods.
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