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Staff Data ScientistHarnham • United States
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Staff Data Scientist

Harnham
  • US
    United States
  • US
    United States
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À propos

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 optimizationDevelop pricing, ranking, and personalization algorithms to improve marketplace performanceApply causal inference and experimentation techniques to optimize decision-makingOwn projects end-to-end: from exploratory analysis and modeling through to production deploymentTranslate complex modeling outputs into clear business insights and recommendationsCollaborate closely with engineering and product teams to operationalize models
Requirements
5+ years of experience in data science or machine learning in a production environmentStrong foundation in statistical modeling and machine learning (e.g., classification, ensemble methods)Experience deploying models into production and iterating based on real-world performanceProficiency in Python and SQLExperience with experimentation, causal inference, or uplift modelingStrong 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 ResearchExperience in fintech, lending, or credit risk modelingExposure to marketplace, pricing, or recommendation systemsFamiliarity with optimization techniques and constrained modeling problems
What Makes This Opportunity Unique
Direct ownership of models that impact revenue and riskHigh visibility role working closely with senior leadershipFast-paced, startup environment with significant autonomyOpportunity 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.
  • United States

Compétences linguistiques

  • English
Avis aux utilisateurs

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