Senior Data Scientist / ML Engineer
About Bitrefill
Bitrefill is the world's leading crypto lifestyle platform. We enable millions of users globally to pay for gift cards, mobile phone refills, and everyday goods using Bitcoin, Lightning Network, and other digital assets. Our long-term goal is to provide everyone with the tools to use crypto as real "digital money" daily — without needing to register for additional services or log into a web platform.
We are now actively building a new product: the Bitrefill crypto card for paying for goods and services in everyday life.
The Role
We are looking for a Senior DS/ML Engineer to help us make data-driven decisions across fraud detection, Lightning Network liquidity optimization, user behavior modeling, and risk scoring for the crypto card.
You won't just build models — you'll help shape the ML infrastructure of a fast-growing crypto-payments startup.
What You'll Do
Fraud & Risk ML — Develop anomaly detection models, transaction scoring for withdrawals, and real-time predictive rules to flag suspicious activity.
Lightning Network optimization — Build models to optimize payment routing, channel liquidity management, and predict channel health.
Crypto card infrastructure — Create credit risk models and user scoring for card issuance without traditional credit history.
LTV & churn prediction — Forecast user behavior to improve retention and conversion, especially in low-crypto-adoption countries.
Product & growth analytics — Develop ML-driven hypotheses for A/B testing and recommendation systems (e.g., which gift cards to offer).
Data pipeline & MLOps — Help build pipelines for training and deploying models to production (alongside engineers).
Requirements
5+ years of experience in Data Science / Machine Learning, ideally in fintech, payments, crypto, or high-throughput transactional systems.
Strong experience building anti-fraud models, time series forecasting (for transactions), LTV predictions, or classification/clustering models.
Python — solid proficiency (pandas, scikit-learn, xgboost/lightgbm; PyTorch/TensorFlow is a plus).
SQL — advanced level.
Experience with Airflow, dbt, or similar ETL/ML pipeline tools.
Understanding of Lightning Network basics (or strong willingness to dive deep within 1–2 weeks).
English — sufficient to discuss ML metrics and business problems fluently.
We Offer
Fully remote work from anywhere in the world (with ~4–6 hours overlap with Stockholm time zone).
Opportunity to build an ML system from scratch in a startup that is truly changing how people use crypto.
Competitive salary + equity (tokens) or profit-sharing.
Minimal bureaucracy — maximum responsibility and freedom.
Work with cutting-edge technologies: Lightning Network and crypto cards.
How to Apply
Send your resume and a link to your GitHub / Kaggle / project where you solved a fraud, time series, or risk modeling problem. Mention if you have experience with Lightning or blockchain analytics — if not, just tell us how quickly you can learn new domains.
