Staff Data Scientist

Own the analytical strategy for Zip’s new product's initiative, serving as the senior analytics partner supporting the development and growth of new financial products from early-stage exploration through scaled adoption. Bring deep product and financial analytics expertise to ambiguous, 0-to-1 problems, establishing the insights, measurement frameworks and analytical foundations needed to guide product strategy, investment decisions, risk trade-offs and sustainable growth. Remote-first opportunity for US-based employees with the option to work in-person out of our Manhattan office Start your adventure with Zip As a Staff Data Scientist, you will leverage your expertise in Data Science to define, architect, build, implement and scale, new ML/AI solutions that push the next frontier of capabilities at Zip. You will be building the first generation of models that leverage rich new data sources and provide the foundation for the next generation of Zip. You will use your extensive experience, mentoring and partnering with more junior data scientists to build best-in-class ML and AI solutions. As a green field opportunity, you will be expected to independently experiment and iterate on solutions and take a test-and-learn approach to your work. You will balance short-term tangible business gains with more long-term ambitious work that together maximize the value for the business. Whatever you build, you will be expected to own end-to-end, and be responsible for communicating with business stakeholders and collaborating with engineering teams on making them work in a production environment. In addition to your extensive experience in Data Science and Financial Services, you are self-driven, intellectually curious, and comfortable iterating on simple solutions that are informed by experimental results. Interesting problems you’ll get to solve Design and build new AI/ML models leveraging bank transaction data to enable new product capabilities Explore open-ended problems within bank transaction data as well as other sources to enable new product capabilities Rapidly experiment, build, and iterate on solutions, providing realistic proofs of concept that can be tested and refined Establish clear evaluation frameworks and decision criteria for what should scale, change, or stop. Provide technical direction to other data scientists on complex workstreams, delegating defined components where appropriate while retaining accountability for technical quality and outcomes Assist with test designs that produce the data necessary to build future versions of your models Balance short-term wins with longer-term experimental work that drive overall value of the business Leverage AI across your entire stack, from boosting productivity to building custom neural network/LLM solutions Build models that mitigate risk while driving profitable growth for the business Work closely with partnering engineering teams to make sure solutions are…