Data Scientist

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.