Data Scientist

Job Description

Staff Data Scientist

Location: New York City (Hybrid)

Compensation: Up to $205,000 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

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• Build and deploy machine learning models for underwriting, credit risk, and portfolio optimization
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• Develop pricing, ranking, and personalization algorithms to improve marketplace performance
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• Apply causal inference and experimentation techniques to optimize decision-making
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• Own projects end-to-end: from exploratory analysis and modeling through to production deployment
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• Translate complex modeling outputs into clear business insights and recommendations
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• 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
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• Strong foundation in statistical modeling and machine learning (e.g., classification, ensemble methods)
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• Experience deploying models into production and iterating based on real-world performance
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• Proficiency in Python and SQL
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• Experience with experimentation, causal inference, or uplift modeling
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• 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
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• Experience in fintech, lending, or credit risk modeling
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• Exposure to marketplace, pricing, or recommendation systems
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• 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
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• High visibility role working closely with senior leadership
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• Fast-paced, startup environment with significant autonomy
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• Opportunity to shape core data science strategy and systems
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• 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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