Staff Data Scientist
HarnhamAbout the role
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
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.
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
Qualifications
- 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
Benefits
- 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
Skills mentioned
About Harnham
Harnham provides specialist Data and AI recruitment and staffing services, along with bespoke training solutions, across multiple industry verticals, operating in the UK, the USA and EU - contact us today to discuss your requirements: info@harnham.com Our recruitment and talent teams cover all aspects of the data and AI pipeline, from collection to consumption, across multiple data roles and functions. Whether you need full-time staff, contract talent, specialized training, Data-qualified graduates, or C-suite executives, Harnham Group is equipped to fulfill all your data talent requirements. Our five core services: * ATD - Rockborne – our graduate development arm – deploys expertly trained data consultants, who have gone through an intensive 12-week data training programme. After two years in the scheme, your consultant could become a * Contract / C2C / Freelance: Whether you're addressing a talent shortage, augmenting a project team, or encountering resource gaps, our specialist consultants offer bespoke interim talent solutions to address your unique challenges and drive success. * Full-Time / Direct Hiring: From early career professionals to senior management, our comprehensive services enable you to unearth outstanding data talent across various specializations, ensuring your organization thrives in the data-driven era. * Executive Search: With our dedicated executive search team and an extensive network encompassing the director to C-suite level, we assist both global corporations and ambitious startups in securing top-tier leadership talent to accomplish their goals. * GenAI, Prompt, LLM Training: Elevate your team's data expertise with our all-encompassing training programs covering essential tools and technologies such as Python, SQL, Machine Learning, LLM’s and AI. Highly bespoke, customised to your team learning requirements and budgets.