Applied Data Scientist, Fintech Initiatives

Role Overview

• 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.

Requirements

• 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.

Tech Stack

• Python
• SQL

Benefits

• Health insurance
• 401(k) matching
• Flexible work hours
• Paid time off
• Remote work options