Staff Data Scientist (Yield Optimization)

TL;DR

Staff Data Scientist (Yield Optimization): Leading the development and implementation of predictive models to optimize offer matching and revenue generation with an accent on funnel optimization and user decision-making. Focus on building recommendation systems and integrating models into the revenue engine to maximize business impact.

Location: Must be based in the US or Canada

Salary: $195,000 – $205,000

Company

hirify.global is a Series A startup rewriting the insurance experience through its licensed agency, Savvy, using a customer-first tech approach.

What you will do

• Drive the full lifecycle of yield optimization models from ideation and development to production monitoring and iteration.
• Partner with Engineering and Business teams to seamlessly integrate models into the recommendation engine.
• Evaluate and improve model accuracy to directly impact key KPIs such as revenue and conversion rates.
• Intelligently match users to the best offers to drive value for the internal agency and external buyers.
• Interface with external partners to align model performance with partner goals.

Requirements

• 7+ years of experience in Data Science roles implementing predictive models.
• Proven end-to-end ownership of predictive models used in production.
• Experience with recommendation systems, ad tech, or yield optimization models.
• Expert proficiency in SQL for sourcing and wrangling data across the full stack.
• Strong business acumen to translate complex revenue problems into clear analytical questions.
• Must be based in the US or Canada

Nice to have

• Experience with ML platforms such as DataRobot.
• Background in Ad Tech or Insurtech.

Culture & Benefits

• Competitive compensation at the 75th percentile (or 90th for SF/NYC).
• Fully remote work environment across the US and Canada.
• Flexible vacation policy and paid parental leave.
• Comprehensive health insurance starting day one, including 401(k), HSA, and FSA contributions.
• Wellness programming and quarterly virtual or in-person team events.