Senior Data Scientist

About the role

OUR MISSION AND VISION

At Solidgate, our mission is clear: to empower outstanding entrepreneurs to build exceptional internet companies. We exist to fuel the builders — the ones shaping the digital economy — with the financial infrastructure they deserve. To achieve that, we’re on a bold path: to become the #1 payments orchestration platform in the world.

We believe the future of payments is shaped by people who think big, take ownership, and bring curiosity and drive to everything they do. That’s exactly the kind of teammates we want on board.

We're building the #1 payment orchestrator in the world — and the names behind us prove it. Our clients include Bolt, Ajax, Nova Post, Megogo and we're a direct partner of Visa and Mastercard with a European acquiring license. Operating in 150+ markets, with a trusting partners like J.P. Morgan.

Solidgate is part of Endeavor https://endeavor.org/ — a global community of the world’s most impactful entrepreneurs. We’re proud to be the first payment orchestrator from Europe to join — and to share our expertise within a network of outstanding global companies.

ABOUT THE TEAM AND ROLE

You’ll join Solidgate’s ML team as a Data Scientist, working closely with the Head of ML and ML Engineers. Your focus will be researching payment data, testing hypotheses, and defining modeling approaches that help the team develop ML solutions faster.

The team works with 20M+ orders and 100M+ transactions a month. Its next big step is real-time ML payment routing. You’ll research how to select an acquiring bank for each transaction and prepare the data and modeling approach for ML Engineers to build on.

Explore our technology stack ➡️ here https://solidgate-tech.github.io/.

WHAT YOU’LL OWN

— Explore transaction data and assess whether it can support a predictive model for a product problem — Develop mathematical and statistical approaches to model research — Define which data is needed and how a model should be trained and evaluated — Formulate hypotheses and design experiments, including A/B tests — Prepare research findings, model requirements, and next steps for ML Engineers — Partner with ML Engineers as they implement and validate models — Track model outcomes and explain their business impact — Work with Product, Engineering, and Data Platform teams on data and MLOps needs

YOU’RE A GREAT FIT IF YOU HAVE

— 4–5+ years of experience in Data Science or ML — Strong mathematical and statistical foundations — Hands-on experience with classical predictive models, such as fraud detection, credit risk, transaction attribution, financial forecasting, recommendations, or pricing — Experience taking ML models into production — Experience designing experiments and A/B tests — Experience with feature engineering on high-cardinality data — A proactive approach to finding a problem, proposing a solution, and moving it forward — Openness to AI and confidence using AI tools

— A driver mindset: you can walk into a greenfield space, figure out what to build, propose it, and own it through delivery — Great communication skills and comfort working with a wide range of stakeholders