Lead Data Scientist (FinTech)

Location: Hybrid, onsite two days per week on Mondays and Thursdays at an office in San Diego, Atlanta, or New York, United States.

Salary: $150,000–$170,000 per year, plus potential incentives, bonus, 401(k) match, and health and welfare benefits.

Company

hirify.global is a fintech lender serving small businesses with working capital and equipment financing, providing more than $3 billion in funding since 1999.

What you will do

• Build targeting, response, propensity, conversion, segmentation, lead-scoring, recommendation, and personalization models for direct mail and digital acquisition.
• Optimize campaigns, offers, channels, and marketing budgets using customer lifetime value, acquisition cost, credit performance, and unit economics.
• Design A/B tests, causal-inference analyses, uplift models, and incrementality measurements.
• Own projects end to end, from data discovery and feature engineering through validation, deployment, monitoring, and iteration.
• Collaborate with marketing, credit risk, sales, product, engineering, and analytics stakeholders to translate commercial questions into measurable outcomes.
• Mentor data scientists, improve modeling and coding standards, and verify AI-assisted analysis, calculations, and model outputs before release.

Requirements

• Master’s degree or higher in a quantitative discipline, or equivalent hands-on experience shipping production models.
• At least 5 years of relevant data science or machine learning experience.
• Strong programming skills in Python or R, with proficiency in SQL and relational databases.
• Experience with supervised and unsupervised machine learning, statistical analysis, model validation, feature engineering, and experimental design.
• Experience deploying, monitoring, and maintaining predictive or recommendation models in live production environments.
• Experience leading end-to-end data science projects, coordinating stakeholders, mentoring data scientists, and applying version control, testing, reproducibility, and documentation.

Nice to have

• Experience in growth data science, marketing analytics, customer acquisition, targeting, propensity modeling, segmentation, recommendation systems, or personalization.
• Experience with direct mail, performance marketing, retention, customer lifetime value, attribution, or offer optimization.
• Experience in fintech, consumer lending, credit risk, underwriting, pricing, AWS, cloud technology, or MLOps.

Culture & Benefits

• Business-casual environment with an energetic and collaborative culture.
• Health insurance for employees and families.
• Matching 401(k) retirement plan and education stipends.
• Professional growth opportunities and employee events throughout the year.