About the role

Role overview

Join Apollo.io as a Staff Data Scientist (Product) to shape product strategy and decision-making using data. You will optimize existing products and support early-stage product initiatives by partnering with cross-functional teams and turning complex data into actionable insights.

Responsibilities

Optimize existing products and support early-stage (0→1) initiatives using data-driven insights.
Collaborate with cross-functional teams to identify key product questions and deliver data-driven solutions.
Develop and maintain scalable, reliable, and accurate analytics infrastructure to enable sound product decisions.
Provide expert analysis to influence product strategy, including deep exploratory work on product funnels and cohorts.

Requirements

Ability to translate complex data into actionable insights for cross-functional stakeholders.
Strong product analytics experience, with a track record of impacting product strategy and decision-making through data.
Expert-level influence on product strategy using SQL, A/B testing, machine learning, and statistical analysis.
Deep experience with exploratory analysis for cohorting, time series analysis, and funnel analysis/optimization.
Experience building/maintaining reliable analytics infrastructure.
Strong communication skills to clearly present findings to both technical and non-technical stakeholders.
Degree in Analytics, Applied Mathematics, Economics, Statistics, or a related field (or equivalent experience).
Essential experience with product analytics tools to track end-to-end journeys/funnels (e.g., Amplitude, Heap, Mixpanel) and analyze events.

Nice-to-haves

Experience supporting SaaS (Product-Led Growth) companies, particularly around activation metrics and aha/habit moments.
Experience with 0→1 product initiatives.
Proficiency with analytics platforms such as Looker and/or Amplitude (tooling is secondary to impact).
Familiarity with R, Python, SAS and related statistical/ML tooling.

About Apollo.io

Apollo.io is a SaaS company operating in the product-led growth space, helping customers through its product and data-driven decisions. The company builds products that rely on analytics and experimentation to optimize activation and growth metrics.