Senior Staff Data Scientist (Machine Learning)

Location: New York, NY; hybrid work with 3 days per week in the office. Illinois-based salary structure is also listed.

Salary: New York: $240,000–$249,500 per year; Illinois: $216,000–$224,500 per year.

Company

hirify.global builds data science and machine learning systems that improve marketplace operations, customer experience, and business decision-making.

What you will do

• Define data science principles, frameworks, and best practices for improving customer, marketplace, and business outcomes.
• Mentor and coach Data Scientists while contributing to technical excellence and career development.
• Analyze interconnected marketplace systems involving customer behavior, fulfillment reliability, ETA accuracy, pricing, supply planning, and product experience.
• Develop causal inference and experimentation frameworks to measure the impact of product, operational, and marketplace changes.
• Partner with engineering on shared data layers, feature pipelines, modeling APIs, experimentation infrastructure, and production ML services.
• Define experimentation strategies and operationalize risk-aware models and insights that improve business metrics.

Requirements

• 8+ years of industry experience with an MS, or 6+ years with a PhD, in Statistics, Economics, Applied Mathematics, Computer Science, Data Science, Machine Learning, or a related quantitative field.
• Experience applying data science and machine learning to complex business problems such as marketplace optimization, customer experience, forecasting, personalization, pricing, supply and demand balancing, operational policy changes, or product experimentation.
• Deep expertise in causal inference, experimentation, and statistical modeling, including A/B testing, difference-in-differences, regression discontinuity, instrumental variables, synthetic controls, uplift modeling, or causal impact analysis.
• Strong understanding of business and product trade-offs involving customer experience, efficiency, ETA confidence, conversion risk, fulfillment reliability, cost, growth, quality, and long-term marketplace health.
• Proficiency in Python, data analysis, visualization, and scalable production-ready code using object-oriented design.
• Experience taking data science, ML, or causal inference systems into production and partnering with engineering on architecture, deployment, and monitoring.
• Fluency in SQL or similar tools for querying production-scale datasets.
• Experience mentoring and providing technical direction to scientists, analysts, or engineers.

Nice to have

• Experience leading end-to-end data science, machine learning, measurement, or experimentation frameworks in marketplace, consumer product, fulfillment, logistics, pricing, forecasting, or operations systems.
• Experience designing causal measurement strategies for complex systems where product, marketplace, and operational decisions interact across multiple layers.
• Background in causal inference, econometrics, Bayesian modeling, experimental design, or observational measurement in high-noise environments.
• Experience with A/B testing, power analysis, heterogeneous treatment effects, guardrail metrics, interference effects, and long-term impact measurement.
• Experience building or influencing production ML systems combining predictive modeling, causal measurement, experimentation, and business rules.
• Ability to align product, engineering, operations, business, and data science around an ML, experimentation, and measurement strategy.
• Experience defining strategy and technical roadmaps for data science, machine learning, experimentation, or causal inference platforms.

Culture & Benefits

• Hybrid work with at least 3 office days per week, with the option to work in the office up to 5 days.
• Equity and a 401(k).
• Medical, dental, and vision plans.
• Company-paid short- and long-term disability coverage, paid time off, vacation, sick leave, and paid parental leave.
• Discounted meals and perks across the hirify.global family of brands.
• Commitment to objective hiring, diversity, equity, and inclusion.

Hiring process

• Interview scheduling and candidacy updates are provided by email or text.
• Accommodation is available during the interview process upon request.