Quantitative Analyst (AI)

Location: Onsite in Warsaw, Poland; candidates must be based in Warsaw or willing to relocate.

Company

hirify.global is an AI teammate that operates in Slack and Microsoft Teams, connects to thousands of tools, and performs work across finance, marketing, operations, and engineering.

What you will do

• Build and improve customer lifetime value models using retention, expansion, usage, and customer characteristics.
• Validate predictions through backtesting, calibration, uncertainty estimation, leakage prevention, and performance monitoring.
• Translate LTV, cost-to-serve, and payback estimates into acquisition, pricing, segmentation, and sales-investment recommendations.
• Model attribution and incrementality across marketing and sales channels using experiments and causal methods.
• Connect customer economics to growth, profit, runway, and fundraising scenarios with explicit sensitivities.
• Develop tested, reproducible Python code and lifecycle dashboards in collaboration with growth, sales, finance, and data engineering.

Requirements

• Strong statistical and quantitative modeling skills, including retention, expansion, and lifetime value analysis.
• Experience with backtesting, calibration, uncertainty estimation, leakage prevention, and changing customer behavior.
• Depth in experimentation, causal inference, attribution, marketing-mix modeling, or incrementality measurement.
• Advanced SQL and strong Python engineering skills for tested and reproducible modeling code.
• Commercial judgment and the ability to explain assumptions, trade-offs, and when evidence is too weak to act.
• Based in Warsaw or willing to relocate; onsite collaboration is required.

Nice to have

• Background in quantitative research, statistics, econometrics, or a related field.
• Experience with customer lifetime value, survival or retention modeling, and SaaS or usage-based economics.
• Experience building an LLM application beyond a demo.

Culture & Benefits

• Small team with high trust, low process, and ownership of meaningful product surfaces.
• Direct collaboration with decision-makers in growth, sales, and finance.
• Opportunity to ship from the first week and speak with users from the first day.
• Models and metric definitions become part of a data layer used by people and AI.
• Top-of-the-market salary.