Data Scientist

Responsibilities

• Own fraud, chargeback and transaction-risk models end to end, from problem framing to feature engineering to production thresholds
• Build and tune machine-learning and signal layers alongside external risk vendors
• Set the strategic direction for risk modelling and lead the team on execution
• Act as a data scientist for the wider business by making data accessible through Snowflake, dashboards, and internal data assistants
• Tackle high-leverage product, growth and experimentation problems as they arise
• Advance internal AI applications, from agentic coding assistants to internal copilots and novel uses of large language models

Requirements

• Strong mathematical and statistical foundations with a drive for hard, quantitative problems
• Self-starter who identifies important problems, scopes them, and acts without waiting to be directed
• Capable engineer and analyst fluent in Python and SQL, able to take models from idea to production
• Intellectual honesty about uncertainty and rigor in evaluating your own work
• Genuine interest in crypto, payments, fraud and the data they generate

Preferred Qualifications

• Track record of exceptional output such as strong academic results, research, competition results, open-source contributions, or widely used personal projects
• Exposure to fraud, risk, payments, crypto, or other adversarial, high-stakes machine learning
• Experience deploying and maintaining models in production, including monitoring and drift
• Depth in experimentation or causal inference
• Habit of building personal tools and automations

About the Company

Transak provides onboarding infrastructure for financial applications through authentication, KYC, risk checks, and fiat on/off ramps. Its API and widget-based solutions are used by partners including MetaMask, Coinbase, Ledger, and Trust Wallet to enable seamless onboarding of over 10 million users across more than 450 active applications.