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Staff Data Scientist (Product)

Apollo.io

Salary not specified
Aug 20, 2025
Remote, US
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Apollo.io is seeking to optimize its product strategy and decision-making through data-driven insights.

Requirements

  • Expertise in translating complex data into insights that are actionable for cross-functional teams
  • Proficiency with data analytics tools and platforms (e.g., Looker, Amplitude)
  • Experience in building and maintaining reliable analytics infrastructures
  • Deep experience in working with exploratory analysis projects related to cohorting, time series analysis, and funnel analysis/optimization
  • Expert-level proficiency in influencing product strategy with SQL, A/B testing, machine learning, statistical analysis, and related tools like R, Python, SAS, etc.
  • Experience with Product Analytics tools to track end-to-end journeys/funnels (e.g., Amplitude, Heap, Mixpanel) and analyzing events within those products
  • Previous or current experience supporting SaaS (Product-Led Growth) companies with uncovering gaps and recalibrating activation metrics (e.g., aha/habit moments)

Responsibilities

  • Translate business needs into data analysis and actionable insights to optimize product performance and user experience
  • Develop and maintain a scalable, reliable, and accurate analytics infrastructure to support product decisions
  • Establish and maintain best practices for data collection, analysis, and reporting
  • Deliver actionable insights and recommendations focused on landing tangible product impact
  • Ensure the integrity and accuracy of the data used for analysis and reporting
  • Support 0 to 1 product launches by identifying key metrics and analyzing early-stage product data when applicable
  • Work closely with cross-functional teams to drive product innovation and optimization through data-driven insights

Other

  • Degree in Analytics, Applied Mathematics, Economics, Statistics, or related analytical field of study, or an equivalent combination of training and experience
  • Excellent communication skills, with the ability to clearly present data insights to both technical and non-technical stakeholders
  • A high level of accountability, a passion for continuous learning, and the ability to thrive in a fast-paced, dynamic environment