Technology
Data Scientist
Kody
Workable
- Location
- Hong Kong, Hong Kong, Hong Kong, Not specified
- Type
- Not specified
- Salary
- Salary not specified
- Posted
- 5 Nov 2026
About Kody Kody is a fast-growing Fintech dedicated to bringing seamless online payments and financial services to brick-and-mortar businesses across the UK, Europe, and APAC. About the Role At Kody, we process high volumes of transaction data daily. We are looking for an intellectually curious, technically seasoned Data Scientist to make sense of our complex data and drive high-impact commercial decisions. You will act as the core quantitative engine for the team—diving into payment success rates, merchant transaction funnels, and revenue metrics. You won’t just pull numbers; you will be responsible for understanding the underlying business mechanics, transforming raw, messy data into actionable insights, and operationalizing machine learning and statistical models directly within our modern data stack (BigQuery & Looker). Key Responsibilities In-Warehouse Data Transformation & Feature Engineering: Rather than pulling raw data into local environments, leverage advanced, highly optimized SQL to perform heavy-duty data transformations, data cleaning, and feature engineering directly within BigQuery’s distributed compute environment. Semantic Layer Integration & BI Architecture (Look
About Kody Kody is a fast-growing Fintech dedicated to bringing seamless online payments and financial services to brick-and-mortar businesses across the UK, Europe, and APAC. About the Role At Kody, we process high volumes of transaction data daily. We are looking for an intellectually curious, technically seasoned Data Scientist to make sense of our complex data and drive high-impact commercial decisions. You will act as the core quantitative engine for the team—diving into payment success rates, merchant transaction funnels, and revenue metrics. You won’t just pull numbers; you will be responsible for understanding the underlying business mechanics, transforming raw, messy data into actionable insights, and operationalizing machine learning and statistical models directly within our modern data stack (BigQuery & Looker). Key Responsibilities In-Warehouse Data Transformation & Feature Engineering: Rather than pulling raw data into local environments, leverage advanced, highly optimized SQL to perform heavy-duty data transformations, data cleaning, and feature engineering directly within BigQuery’s distributed compute environment. Semantic Layer Integration & BI Architecture (Looker): You won’t just output model scores to a database—you will integrate model outputs directly into our Looker environment. Build and maintain Looker Studio dashboards that give non-technical colleagues reliable metrics, experiment results and model outputs. Deep-Dive Commercial & Funnel Analytics: Independently analyze petabyte-scale payment transaction and merchant telemetry datasets to uncover operational bottlenecks, drop-offs, and revenue growth levers. Core Metrics Definition & Governance: Partner closely with Commercial, Operations, and Product leaders to define, standardize, and govern business KPIs and experimentation frameworks across regional markets. Advanced Statistical & Predictive Modeling: Develop production-ready statistical and machine learning models (e.g., merchant churn, fraud anomaly detection, transaction routing optimization); implement rigorous validation and data quality frameworks. Executive Decision Support: Deliver fast, data-backed strategic analyses, supporting senior management and C-suite leadership with scenario planning, unit economics, and performance forecasting. Requirements Experience Level: Minimum 5+ years of professional, hands-on experience in data science, advanced business intelligence, or quantitative analytics within a commercial, fast-paced environment. (Note: This is a senior role requiring proven independent execution). Strong Academic Foundation: Bachelor’s or Master’s degree from a top-tier university in Statistics, Mathematics, Computer Science, Data Science, Quantitative Finance, or a related quantitative discipline. Expert-Level SQL & Cloud Data Warehousing: Expert-level SQL capabilities (complex analytical window functions, CTEs, query plan optimization) with hands-on experience leveraging Google BigQuery’s distributed compute environment for large-scale transformations. BI and Data Modelling: Strong experience building dashboards in Looker Studio or a comparable tool; DBT experience is an advantage. Sound grasp of experiment design, significance and separating mix effects from rate effects. Senior Business Acumen & Stakeholder Management: Proven track record of interfacing directly with senior stakeholders, translating abstract business questions into quantitative solutions and articulating technical results into clear commercial actions. Nice to have: Payments or fintech experience (acquiring, interchange, FX); Python; Benefits Why Join Us? Highly Competitive Rewards: Market-leading compensation package designed to reward top talent. High-Trust, Collaborative Team: Work alongside driven, supportive peers in an open and united team culture. Direct & Efficient Communication: Direct feedback, quick decision-making, and zero unnecessary red tape. Immense Growth Potential: Be part of a high-growth fintech journey with expansive career upside.