Staff Data Scientist

Own the analytical strategy for Zip’s Smoothing initiative, serving as the senior analytics partner supporting the development and growth of new financial products, including cash advances and rent advances, 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

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 scalable and stable
Act as a primary technical owner and point of contact for the family of models in this business domain, advising senior stakeholders on model trade-offs and implications 

Advanced degree (PhD preferred) in a quantitative field (e.g., Mathematics, Physics, Social Science, Computer Science)
7+ years of experience in Data Science (can include PhD work)
4+ years of experience in Data Science in Financial Services
Self-starter mentality with strong problem-solving and research skills; able to work independently to drive solutions
Solid grasp of the fundamentals of probability, statistics, and applied research methods
Experience working with cashflow data (e.g., Plaid, MX, Finicity) 
Proficiency in Python and SQL; hands-on experience with Spark/PySpark a plus 
Experience with Neural Networks, LLMs, GenAI 
Experience with credit and/or fraud risk a plus
Proven track record managing large-scale projects end-to-end
Ability to thrive in a fast-paced, multi-tasking environment

Zip is a place where you’ll get out what you put in. The newness of our sector means we need to move at pace and embrace change, and our promise to you when you join the team is that you’ll feel empowered and trusted to make big things happen quickly. 
We want you to feel welcome and as though you have the support to be yourself, and care for yourself at work. Because it’s important to us that you make the most of the opportunities you’ll get to grow your skills and your career, and be surrounded by smart, friendly people and leaders that have your back.
We think these are just some of the best things about being a Zipster. We will also offer you:
Flexible working culture
Incentive programs
Unlimited PTO
Generous paid parental leave
Leading family support policies
Company-sponsored 401k match
Learning and wellness subscription stipend
Beautiful Union Square office with a casual dress code
Industry-leading, employer-sponsored insurance for you and your dependents, with several 100% Zip-covered choices available

Zip is committed to a straightforward and transparent pay structure. The actual base salary will be determined by various individualized factors, including job-related knowledge, skills, experience, location, internal equity, as well as other objective business considerations.
The annual