Senior Finance Data Scientist

Capital on Tap

Greater London

Hybrid

GBP 90,000 - 130,000

Full time

14 days+

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Benefits offered by this job

Private Healthcare

Worldwide travel insurance

Reproductive health platform access

Sabbatical program

Pension scheme

Octopus EV salary sacrifice scheme

28 days holiday

Learning and wellbeing budget

Parental leave

Cycle to Work

Season Ticket Loan

Therapy sessions

Dog friendly offices

Free drinks and snacks

Job summary

Capital on Tap is hiring a Senior Data Scientist in London to join our Finance team. You’ll own IFRS9 ECL and portfolio modelling, spanning UK and US revolving credit books, reporting to Head of FP&A. Use Snowflake, dbt, Fivetran, and Python to build and calibrate models, deliver forecast-ready inputs, and collaborate with Finance, Risk and Data Science in a hybrid setup.

Qualifications

2-5+ years building statistical/credit risk models in Python and SQL.
Experience IFRS9 ECL modelling (PD/LGD/EAD) or willingness to develop quickly.
Commercial understanding of revolving credit economics (utilisation, arrears, default, recoveries).
End-to-end work from analysis and calibration to production forecast inputs.

Responsibilities

Own IFRS9 ECL and portfolio modelling workstreams across UK and US revolving credit books.
Build, calibrate, implement and monitor IFRS9 models (PD, LGD, EAD), including macro overlays.
Develop and maintain the portfolio model that feeds the financial model and forecast inputs.
Collaborate with FP&A, Risk and other stakeholders to ensure model outputs land in the forecast.
Apply AI tools confidently across the workflow and promote practical AI adoption.

Skills

Python

SQL

IFRS9 ECL

Credit risk modelling

Tools

Snowflake

dbt

Fivetran

Kubernetes on Azure

JupyterLab

Omni

Job description

We're Capital on Tap

Capital on Tap started because small businesses were underserved. Big banks were slow, their products weren't fit for purpose, and small business owners often couldn't access what they needed. We set out to fix that.

Today we're a financial platform - not just a credit card company. We offer a best-in-class business credit card, SME-focused spend management platform, a savings product that hit £1 billion in funds within its first year, and a growing suite of tools and financial products that make running a small business easier.

1,000+ employees, £20bn in annual card spend, 200,000+ customers, 17,000+ Trustpilot reviews averaging 4.7 stars, and we're profitable. We’ve done a pretty good job so far, but we’re just getting started!

This is a Hybrid role, working from our London (Moorgate) offices 3 days per week.

Finance at Capital on Tap

Our Finance team sits at the heart of everything we do, working across our UK and US entities and collaborating closely with the rest of the business to keep our financial foundations solid as we grow. We're a lean, high-ownership team - you'll get real breadth across the finance function and plenty of room to shape how things are done as we scale.

What You'll Be Doing

We're hiring a Senior Data Scientist to join Capital on Tap, reporting to the Head of FP&A.

You’ll own two linked workstreams - IFRS9 Expected Credit Loss (ECL), and portfolio modelling that feeds the financial model to produce forecasts. The work spans the UK and US revolving credit books, sitting close to Finance, Risk and Data Science.

Tech stack: Snowflake, dbt, Fivetran, Python, JupyterLab, Omni, and Kubernetes on Azure.

ECL

Build, calibrate, implement and monitor IFRS9 models (PD, LGD, EAD), including staging/SICR logic and macroeconomic overlays.
Run and harden month-end ECL production - scenario runs, combined outputs, and result checks into Snowflake.

Portfolio Modelling

Develop and maintain the portfolio model that feeds the financial model - active customers, balances, funding, repayments, finance charges and bad debt.
Diagnose drift, recalibrate assumptions and overlays, and deliver forecast inputs Finance can trust.

Across Both

Partner with FP&A, Risk and other stakeholders so model outputs land cleanly in the financial forecast, without unnecessary process or IT complexity.
Use AI tools confidently across the workflow, and help the team adopt practical AI-assisted ways of working.

We're Looking For

2-5+ years building statistical/credit risk models in Python, and extracting and shaping data in SQL.
Credit risk modelling experience, ideally IFRS9 ECL (PD/LGD/EAD), staging and model monitoring - or a clear desire to build that expertise quickly.
Commercial understanding of revolving credit economics (utilisation, arrears, default, recoveries, portfolio growth).
Comfort working end-to-end - from analysis and calibration through to production runs and stakeholder-ready forecast inputs.
Curiosity and judgement in applying AI to modelling and engineering work, while keeping outputs explainable and controlled.
Ability to work autonomously with strong judgement and proactivity in a small team.

Nice to Have

Experience with some of our stack is helpful - Snowflake, dbt, Fivetran, Python, JupyterLab, Omni, Kubernetes on Azure.
Experience feeding portfolio/behavioural models into an FP&A or financial planning model.
Familiarity with LightGBM or similar gradient-boosted models for behavioural forecasts.
Exposure to model change control, independent validation, or year-end ECL disclosure packs.
Prior work across both UK and US (or multi-region) credit portfolios.

Diversity & Inclusion

We welcome, consider and encourage applications from anyone who shares our commitment to inclusivity. Join us in creating a space where authenticity thrives, and everyone can do their best work.

Great Work Deserves Great Perks