We Love AI JobsData Scientist
HarnhamJoin a high-growth fintech and e-commerce platform as a Staff Data Scientist, where you'll directly influence revenue-driving systems through machine learning models. Work in a lean, technical team environment that fosters innovation and offers significant autonomy, all while shaping the company's data science strategy.
Skills & Expertise
Key Responsibilities
Build and deploy machine learning models for underwriting and credit risk.
Develop algorithms for pricing and marketplace performance improvement.
Translate complex outputs into clear business insights and recommendations.
Full Description
Staff Data Scientist
Location: New York City (Hybrid)
Compensation: Up to $250,000 base + bonus + equity
Company Overview
A high-growth consumer fintech and e-commerce platform is building the credit infrastructure powering digital commerce in a large, underserved market. The business has reached profitability, processes hundreds of millions in annual transaction volume, and continues to scale rapidly with strong backing from top-tier investors.
The team is lean, highly technical, and composed of leaders from globally recognized technology and marketplace companies. This is an opportunity to join at a pivotal stage and directly influence core revenue-driving systems.
The Role
As a Staff Data Scientist, you will play a critical role in developing and deploying machine learning models that directly impact the company’s P&L. You’ll work across credit risk, pricing, and marketplace optimization problems, owning the full lifecycle from problem definition through to production.
This is a highly cross-functional role partnering with engineering, product, and leadership to drive data-informed decisions and scalable modeling solutions.
Key Responsibilities
* Build and deploy machine learning models for underwriting, credit risk, and portfolio optimization
* Develop pricing, ranking, and personalization algorithms to improve marketplace performance
* Apply causal inference and experimentation techniques to optimize decision-making
* Own projects end-to-end: from exploratory analysis and modeling through to production deployment
* Translate complex modeling outputs into clear business insights and recommendations
* Collaborate closely with engineering and product teams to operationalize models
Requirements
* 5+ years of experience in data science or machine learning in a production environment
* Strong foundation in statistical modeling and machine learning (e.g., classification, ensemble methods)
* Experience deploying models into production and iterating based on real-world performance
* Proficiency in Python and SQL
* Experience with experimentation, causal inference, or uplift modeling
* Strong problem-solving skills with the ability to operate in ambiguous, fast-paced environments
Preferred Background
* Advanced degree (PhD or Master’s) in a quantitative field such as Statistics, Mathematics, Economics, or Operations Research
* Experience in fintech, lending, or credit risk modeling
* Exposure to marketplace, pricing, or recommendation systems
* Familiarity with optimization techniques and constrained modeling problems
What Makes This Opportunity Unique
* Direct ownership of models that impact revenue and risk
* High visibility role working closely with senior leadership
* Fast-paced, startup environment with significant autonomy
* Opportunity to shape core data science strategy and systems
* If you’re excited by building high-impact machine learning systems in a fast-moving environment and want to see your work directly drive business outcomes, this is a unique opportunity to do so at scale.