Applied Data Scientist, Fintech Initiatives

About this role

<h3><strong>What Do We Do?</strong></h3> <p>Triple Whale is the AI operating system built for modern ecommmerce. We help you see what's actually working in your business, what's not, and what to do next. Then we take action for you — pausing the underperforming ad, generating the next batch of creative, flagging the inventory risk before it bites.</p> <p>We pull every signal in your business into one place, and put it on the most trusted measurement foundation in the industry. And on top of that, we give you the most actionable AI in commerce — Moby 2 — letting you tap any LLM you want, grounded in the full context of your business. Moby 2 doesn't just surface insights, it executes decisions for you, with automations that make the rest of your stack smarter.</p> <p>The result: more than 60,000 brands like Pressed Juicery, OUAI, and True Classic turn mountains of complex data into actions that actually grow profit, at a speed and scale that is not humanly possible.</p> <h3><strong>Why Triple Whale Needs You:</strong></h3> <p>Triple Whale has strong product–market fit and a growing base of ecommerce merchant data that most fintech lenders can only dream about. We're now building on that asset to launch financial products — capital access, growth financing, and smarter operating tools — designed specifically for the brands we serve.</p> <p>We're looking for an Applied Data Scientist to own the data science strategy behind this initiative.<br>This is a high-ownership, senior role sitting at the intersection of product, data science, and capital markets. You'll build statistical and ML models end to end — from conception through production — and turn complex financial-product questions into reliable, customer-facing decisioning systems. You'll work across Product, Engineering, Finance, Operations, Legal, and external capital partners to define how Triple Whale evaluates financial-product opportunities, manages risk, measures performance, and scales responsibly.</p> <p>The right person brings strong modeling depth, sharp product judgment, and the business context to work in ambiguity. Fintech, lending, credit, or risk experience is strongly preferred — but we're also open to senior data scientists from adjacent domains who've built high-stakes models in complex, data-rich environments.</p> <h3><strong>What You’ll Do:</strong></h3> <ul> <li>Own the end-to-end data science strategy for Triple Whale's financial products — from roadmap and model development to production deployment and governance.</li> <li>Build models and decisioning frameworks across the full lending lifecycle: merchant eligibility, underwriting, risk assessment, repayment behavior, and growth forecasting.</li> <li>Translate Triple Whale's ecommerce, revenue, marketing, and operational data into actionable signals that power financial-product decisions and partner evaluations.</li> <li>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.</li> <li>Design measurement frameworks that span funnel performance, repayment outcomes, customer adoption, partner performance, and long-term unit economics.</li> <li>Establish model validation, monitoring, and governance practices appropriate for high-stakes financial decisioning.</li> <li>Define the long-term fintech data science roadmap — what to build internally, what to partner on, and where modeling can create durable competitive advantages.</li> </ul> <h3><strong>What You’ll Bring:</strong></h3> <ul> <li>6+ years of applied data science, machine learning, quantitative modeling, or related experience.</li> <li>Ability to work from our Jerusalem office (located in the Central Bus Station next to the train) 2 times a week (Monday &amp; Wednesday) is required</li> <li>Experience leading complex data science initiatives from ambiguous business problems through model design, validation, deployment, and iteration.</li> <li>Strong modeling depth across areas such as predictive modeling, risk modeling, forecasting, classification, causal inference, experimentation, or statistical decisioning.</li> <li>Strong Python and SQL skills, with experience working in production or production-adjacent data environments.</li> <li>Ability to build models that are not just accurate, but explainable, monitorable, and useful to business operators.</li> <li>Strong product judgment and ability to partner with Product and Engineering on customer-facing or internal decisioning systems.</li> <li>Comfort working with cross-functional stakeholders, including executives, Finance, Legal, Operations, and external partners.</li> <li>Excellent communication skills, especially the ability to explain technical tradeoffs, model limitations, and business implications clearly.</li> <li>Ability to operate with high ownership in an early-stage initiative where the roadmap is still being defined.</li> </ul> <h3><strong>Bonus Points If You Bring:</strong></h3> <ul> <li>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.</li> <li>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.</li> <li>Familiarity with model governance, explainability, compliance-aware analytics, and responsible deployment in regulated or high-trust environments.</li> <li>Hands-on work with merchant, ecommerce, marketplace, payments, or revenue data.</li> <li>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.