Applied Data Scientist

What Do We Do? Triple Whale is the complete intelligence platform for ecommerce, helping brands stop guessing and start knowing what’s actually driving growth, what’s wasting money, and what to do next — with total confidence. By pulling all of a company’s data into one place, delivering measurement tools teams can actually trust, and applying the smartest AI in the industry, Triple Whale turns fragmented data into clear insights and actionable recommendations. That intelligence can then be put to work through AI agents and automations that generate creative assets, take action across marketing channels, and make every tool in their stack smarter and more effective. More than 60,000 ecommerce brands including Pressed Juicery, OUAI, and True Classic trust Triple Whale to grow faster and drive revenue with fewer resources by uncovering opportunities and acting on them at a scale that would be impossible manually. Why Triple Whale Needs You: We’ve reached a strong product–market fit and are scaling rapidly — which means marketing measurement, experimentation, and optimization are becoming more complex and more critical than ever. As privacy changes, fragmented signals, and multi‑channel marketing continue to evolve, brands need sophisticated, production‑grade marketing science they can actually trust. We’re looking for an Applied Data Scientist to help us build and scale the core marketing science products that power our platform. This role sits at the intersection of data science and engineering: owning statistical models end to end, deploying them into production, and turning advanced analytics into reliable, customer‑facing capabilities. Your work will directly influence how thousands of brands measure ROI and allocate millions in marketing spend. What You’ll Do: Build marketing measurement and optimization products (e.g., attribution models, MMM, incrementality testing, forecasting systems) Develop and deploy statistical and machine learning models to production Create scalable data pipelines and APIs that serve real-time analytics Partner closely with Product, Engineering, and other stakeholders to translate business questions into clear analytical solutions. Own features end to end from statistical design and validation through deployment, monitoring, and iteration. What You’ll Bring: 4–7 years of experience in applied data science 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 Strong Python skills (pandas, scikit-learn, statistical libraries) Experience deploying models to production (not just notebooks) Solid statistics and machine learning fundamentals SQL and database experience Experience in building APIs or backend services Bachelor's or Master's in a quantitative field (Statistics, CS, Math, Machine Learning/Data Science) Strong English communication skills with technical and non-technical audiences Self-starter comfortable with ambiguity and autonomy Bonus Points If You Bring: Marketing analytics background (attribution, experimentation, measurement) Bayesian statistics or causal inference experience Cloud platform knowledge (GCP, AWS, or Azure) Time series analysis and forecasting Why You’ll Love This Role: This role offers true end‑to‑end ownership from statistical design to production deployment and real customer impact. It’s not pure modeling and not pure engineering, but a blend of both, focused on solving real marketing problems at scale. You’ll work on high‑impact systems that directly shape how businesses understand performance and invest their budgets, all within a fast‑moving, product‑driven environment where your work ships quickly and matters immediately. Our Values 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 compet