Financial Data Scientist

Financial Data Scientist

Madrid, Spain

Twinco is trade finance, re-engineered.

We serve global corporates, making supply chain finance faster, fairer, and more accessible. We do this by combining three capabilities no one else brings together: technology — a modular platform that allows customers to manage all supply chain finance in one place, fully integrated into their commercial workflow; capital — our own balance sheet, so we fund suppliers from the purchase order, not just at invoice stage but earlier, where banks won't go; and risk intelligence — a proprietary underwriting model built on real supplier performance data in emerging markets. The result is lower cost of supply, less disruption risk, and stronger, more competitive supply chains that include suppliers — both large and small, from across the world.

Twinco is a European, fast-growing fintech at scale-up stage, backed by institutional investors, and growing from ~40 to ~60 people in 2026.

We are looking for people who want to build something meaningful at scale, take ownership early, and work at the intersection of finance, technology, and global trade.

POSITION OVERVIEW

About the role

This role will be part of the Data Strategy & Modelling team, reporting directly to the Head of Data Strategy & Modelling. You will work closely with data engineers, data analysts, and other members of the data team.

At the core of Twinco's data architecture sits a proprietary system that structures all of the company's transactional data — every financing event, every payment, every fee — into a single, coherent accounting ledger. This ledger is the source of truth for the business: all data analysis, financial modelling, KPI reporting, and management information ultimately depend on it. It is a double-entry bookkeeping system implemented in Python that tracks financing transactions across the full trade lifecycle, managing 50+ accounts across assets, liabilities, revenue, and clearing accounts.

As a Financial Data Scientist, you will own this system. You will be the person who understands how every financial event in the business translates into structured data — and you will directly propose modifications on the Python codebase to reflect changes in business rules, new event types, or corrections to existing logic. You are not expected to build data pipelines or infrastructure from scratch, but you must be able to read, maintain and evolve our accounting system through code. The broader data pipeline runs on dbt and AWS, managed by the data engineering team — your focus will be on the accounting logic itself.

This is not an isolated technical role. The ledger underpins investor reporting, risk modelling, and operational dashboards, so you will regularly interact with stakeholders across the company and translate business changes into accurate data structures.

We are looking for someone who combines solid accounting fundamentals with enough technical fluency to work inside a codebase — and who wants a hands-on role with direct impact on the accuracy of Twinco's financial reporting and data-driven decision-making.

Key Responsibilities

• Own the functional understanding of Twinco's accounting ledger — the single source of truth for all transactional data in the company.
• Directly modify the ledger's Python codebase to implement changes in business rules, add new event handlers, adjust account mappings, or correct existing logic.
• Validate ledger outputs and investigate discrepancies — ensuring double-entry integrity, accurate balances, and traceability from reported figures back to source events.
• Understand how downstream processes (financial reporting, KPI dashboards, risk models, investor reporting) consume ledger data, and ensure changes are consistent with their needs.
• Collaborate with the data engineering team to define and communicate changes that require deeper technical work (pipeline architecture, Spark optimisation, infrastructure).
• Work with stakeholders across the business — finance, operations, risk — to understand new products, changing commercial terms, or evolving workflows, and assess their impact on the ledger structure.
• Document accounting rules and business logic decisions; write and maintain tests to ensure ledger accuracy across edge cases.

Key Skills Required

• Degree in Economics, Finance, or Accounting with postgraduate training in Data Science or quantitative methods — or conversely, a degree in Mathematics, Statistics, or Data Science with postgraduate training in Finance or Accounting.
• Solid understanding of double-entry bookkeeping.
• Working proficiency in Python — able to read, understand, and modify existing code.
• Strong analytical