Applied Data Scientist, Fintech Initiatives - Triplewhale

Own the end-to-end data science strategy for Triple Whale's financial products - from roadmap and model development to production deployment and governance. Build models and decisioning frameworks across the full lending lifecycle: merchant eligibility, underwriting, risk assessment, repayment behavior, and growth forecasting. Translate Triple Whale's ecommerce, revenue, marketing, and operational data into actionable signals that power financial-product decisions and partner evaluations. Partner with Product, Engineering, Finance, Legal, and Operations to turn analytical work into scalable data products, APIs, internal tools, and explainable recommendations that hold up in commercial and regulatory contexts. Design measurement frameworks that span funnel performance, repayment outcomes, customer adoption, partner performance, and long-term unit economics. Establish model validation, monitoring, and governance practices appropriate for high-stakes financial decisioning. Define the long-term fintech data science roadmap - what to build internally, what to partner on, and where modeling can create durable competitive advantages. 6+ years of applied data science, machine learning, quantitative modeling, or related experience. Ability to work from our Jerusalem office (located in the Central Bus Station next to the train) 2 times a week (Monday & Wednesday) is required Experience leading complex data science initiatives from ambiguous business problems through model design, validation, deployment, and iteration. Strong modeling depth across areas such as predictive modeling, risk modeling, forecasting, classification, causal inference, experimentation, or statistical decisioning. Strong Python and SQL skills, with experience working in production or production-adjacent data environments. Ability to build models that are not just accurate, but explainable, monitorable, and useful to business operators. Strong product judgment and ability to partner with Product and Engineering on customer-facing or internal decisioning systems. Comfort working with cross-functional stakeholders, including executives, Finance, Legal, Operations, and external partners. Excellent communication skills, especially the ability to explain technical tradeoffs, model limitations, and business implications clearly. Ability to operate with high ownership in an early-stage initiative where the roadmap is still being defined. Background in fintech, lending, credit, underwriting, risk, payments, banking, insurance, capital markets, or financial-services data science - ecommerce, DTC, retail, or merchant financing experience is a plus. Proven track record building or evaluating models used in financial decisioning, eligibility, pricing, fraud/risk, or portfolio performance - including time-series forecasting, repayment modeling, or cash-flow modeling. Familiarity with model governance, explainability, compliance-aware analytics, and responsible deployment in regulated or high-trust environments. Hands-on work with merchant, ecommerce, marketplace, payments, or revenue data. Has evaluated third-party data providers, fintech platforms, lenders, or capital partners from a data and risk perspective; familiarity with partner integrations, decision APIs, or embedded-finance products is a plus. Has built or scaled an analytical function, operating model, or roadmap for a new product line. We Are Customer Obsessed : From our mission to every detailed project, everything we do is designed to create a positive impact for our customers. We Move (Very!) Quickly : The speed at which we work, iterate, and deliver value is our most competitive advantage. We Are Trustworthy : Candor, directness, and honest communication helps us learn, grow and improve so we can win together. We Are Curious : We extend beyond our comfort zone and ask questions that guide us towards new, creative, and bold paths. We Act Like A Mensch : We act with honor, integrity and empathy, and have deep respect for our customers and each other.

Own the end-to-end data science strategy for Triple Whale's financial products - from roadmap and model development to production deployment and governance. Build models and decisioning frameworks across the full lending lifecycle: merchant eligibility, underwriting, risk assessment, repayment behavior, and growth forecasting. Translate Triple Whale's ecommerce, revenue, marketing, and operational data into actionable signals that power financial-product decisions and partner evaluations. Partner with Product, Engineering, Finance, Legal, and Operations to turn analytical work into scalable data products, APIs, internal tools, and explainable recommendations that hold up in commercial and regulatory contexts. Design measurement frameworks that span funnel performance, repayment outcomes, customer adoption, partner performance, and long-term unit economics. Establish model validation, monitoring, and governance practices appropriate for high-stakes financial decisioning. Define the long-term fintech data science roadmap - what to build internally, what to partner on, and where modeling can create durable competitive advantages.

Own the end-to-end data science strategy for Triple Whale's financial products - from roadmap and model development to production deployment and governance. Build models and decisioning frameworks across the full lending lifecycle: merchant eligibility, underwriting, risk assessment, repayment behavior, and growth forecasting. Translate Triple Whale's ecommerce, revenue, marketing, and operational data into actionable signals that power financial-product decisions and partner evaluations. Partner with Product, Engineering, Finance, Legal, and Operations to turn analytical work into scalable data products, APIs, internal tools, and explainable recommendations that hold up in commercial and regulatory contexts. Design measurement frameworks that span funnel performance, repayment outcomes, customer adoption, partner performance, and long-term unit economics. Establish model validation, monitoring, and governance practices appropriate for high-stakes financial decisioning. Define the long-term fintech data science roadmap - what to build internally, what to partner on, and where modeling can create durable competitive advantages. 6+ years of applied data science, machine learning, quantitative modeling, or related experience. Ability to work from our Jerusalem office (located in the Central Bus Station next to the train) 2 times a week (Monday & Wednesday) is required Experience leading complex data science initiatives from ambiguous business problems through model design, validation, deployment, and iteration. Strong modeling depth across areas such as predictive modeling, risk modeling, forecasting, classification, causal inference, experimentation, or statistical decisioning. Strong Python and SQL skills, with experience working in production or production-adjacent data environments. Ability to build models that are not just accurate, but explainable, monitorable, and useful to business operators. Strong product judgment and ability to partner with Product and Engineering on customer-facing or internal decisioning systems. Comfort working with cross-functional stakeholders, including executives, Finance, Legal, Operations, and external partners. Excellent communication skills, especially the ability to explain technical tradeoffs, model limitations, and business implications clearly. Ability to operate with high ownership in an early-stage initiative where the roadmap is still being defined. Background in fintech, lending, credit, underwriting, risk, payments, banking, insurance, capital markets, or financial-services data science - ecommerce, DTC, retail, or merchant financing experience is a plus. Proven track record building or evaluating models used in financial decisioning, eligibility, pricing, fraud/risk, or portfolio performance - including time-series forecasting, repayment modeling, or cash-flow modeling. Familiarity with model governance, explainability, compliance-aware analytics, and responsible deployment in regulated or high-trust environments. Hands-on work with merchant, ecommerce, marketplace, payments, or revenue data. Has evaluated third-party data providers, fintech platforms, lenders, or capital partners from a data and risk perspective; familiarity with partner integrations, decision APIs, or embedded-finance products is a plus. Has built or scaled an analytical function, operating model, or roadmap for a new product line. We Are Customer Obsessed : From our mission to every detailed project, everything we do is designed to create a positive impact for our customers. We Move (Very!) Quickly : The speed at which we work, iterate, and deliver value is our most competitive advantage. We Are Trustworthy : Candor, directness, and honest communication helps us learn, grow and improve so we can win together. We Are Curious : We extend beyond our comfort zone and ask questions that guide us towards new, creative, and bold paths. We Act Like A Mensch : We act with honor, integrity and empathy, and have deep respect for our customers and each other.