Data Scientist
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Before you apply
LocationHong Kong, Hong Kong, Hong Kong
Typefull-time
SenioritySenior
Experience5+ yrs
DepartmentTechnology
Company size201–500 people
PostedNov 5, 2026 · 2d ago
Verified live14h ago
At a glanceSummarised by Seekless from the posting.
Minimum 5+ years of professional, hands-on experience in data science, advanced business intelligence, or quantitative analytics in a commercial, fast-paced environment
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
Exceptional, expert-level SQL capabilities (complex joins, CTEs, window functions, and database performance optimization)
Extensive practical experience using Python (pandas, NumPy) or R for exploratory data analysis, pipeline automation, and statistical modeling
Proven track record implementing scalable enterprise BI solutions with Google Looker and/or Power BI
Proven track record of interfacing directly with senior stakeholders, articulating technical and statistical conclusions into clear business actions
Hands-on LookML development experience
Prior analytics experience in Fintech, Merchant Acquiring, Payments, E-commerce, or high-growth tech scale-ups
Hands-on experience with modern cloud data warehouses (BigQuery, Snowflake) and transformation frameworks (dbt)
Familiarity with payment-specific metrics (TPV, take rates, interchange fees, chargeback ratios, authorization rates)
Skills
Google Looker
Power BI
SQL
Python
R
pandas
NumPy
LookML
BigQuery
Snowflake
dbt
Benefits
Competitive compensation
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 building intuitive, scalable dashboards in Google Looker and Power BI.
Key Responsibilities
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Deep-Dive Data Analysis & Ownership: Independently extract, clean, and model high-volume payment transaction and merchant data to uncover operational bottlenecks, drop-offs, and revenue growth levers.
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BI Architecture & Dashboarding: Architect, build, and maintain production-grade semantic models and dashboards in Google Looker (LookML) and Power BI, ensuring metrics are automated, self-serve, and aligned across leadership.
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Core Metrics Definition: Partner closely with Commercial, Operations, and Product executives to establish, standardize, and govern business KPIs across regional markets.
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Advanced Data Modeling: Write robust, production-optimized SQL queries and Python scripts to aggregate complex, petabyte-scale datasets; implement data quality and validation frameworks.
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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
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Experience Level: Minimum 5+ years of professional, hands-on experience in data science, advanced business intelligence, or quantitative analytics in a commercial, fast-paced environment. (Note: This is a senior role requiring proven independent execution).
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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.
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Advanced SQL Expertise: Exceptional, expert-level SQL capabilities (complex joins, CTEs, window functions, and database performance optimization) querying large-scale, multi-table production relational and analytical databases.
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Production Python / R: Extensive practical experience using Python (pandas, NumPy) or R for exploratory data analysis, pipeline automation, and statistical modeling.
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Enterprise BI & Semantic Modeling: Proven track record implementing scalable enterprise BI solutions with Google Looker (hands-on LookML development experience is strongly preferred) and/or Power BI; demonstrated ability to translate vague business needs into self-serve analytical products.
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Senior Business Acumen & Communication: Proven track record of interfacing directly with senior stakeholders, articulating technical and statistical conclusions into clear business actions.
Nice to Have
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Prior analytics experience in Fintech, Merchant Acquiring, Payments, E-commerce, or high-growth tech scale-ups.
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Hands-on experience with modern cloud data warehouses (BigQuery, Snowflake) and transformation frameworks (dbt).
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Familiarity with payment-specific metrics (TPV, take rates, interchange fees, chargeback ratios, authorization rates).
Benefits
Why Join Us?
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Highly Competitive Rewards: Market-leading compensation package designed to reward top talent.
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High-Trust, Collaborative Team: Work alongside driven, supportive peers in an open and united team culture.
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Direct & Efficient Communication: Direct feedback, quick decision-making, and zero unnecessary red tape.
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Immense Growth Potential: Be part of a high-growth fintech journey with expansive career upside.