Job Description
Staff Data Scientist
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Location: New York City (Hybrid)
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Compensation: Up to $205,000 base + bonus + equity
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Company Overview
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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.
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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.
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The Role
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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.
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This is a highly cross-functional role partnering with engineering, product, and leadership to drive data-informed decisions and scalable modeling solutions.
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Key Responsibilities
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- 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
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Requirements
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- 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
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Preferred Background
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- 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
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What Makes This Opportunity Unique
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- 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.
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