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Senior Data Scientist (Product)

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Onsite

Senior Data Scientist (Product)

Apollo.io

Senior Data Scientist (Product)

Skills

SQL QueriesLookerPythonProduct StrategyRAmplitudeData AnalysisMachine Learning

2 months ago

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Important information


Contract type:

Permanent

Salary:

$140,000 – $200,000 / year

Location:

United States

Work mode:

Onsite

Published on:

28 August 2026

What they need


  • We are seeking a highly analytical and impact-driven Senior Data Scientist to help shape our product strategy and decision-making through data
  • In this role, you will focus on optimizing existing products while also supporting early-stage product initiatives where relevant
  • You will work closely with cross-functional teams to drive product innovation and optimization through data-driven insights
  • This position requires a passion for transforming data into actionable insights and the ability to thrive in a fast-paced environment
  • Translate business needs into data analysis and actionable insights to optimize product performance and user experience for both existing and new products
  • Work closely with product managers, engineers, and other cross-functional stakeholders to identify critical product questions and provide data-driven solutions
  • 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
  • Help foster a culture of data-driven decision-making and continuous improvement within the product teams
  • Ensure the integrity and accuracy of the data used for analysis and reporting
  • While the primary focus is on existing products, support 0 to 1 product launches by identifying key metrics and analyzing early-stage product data when applicable

Benefits

  • Remote & in-person roles: Work from wherever you thrive, with all the tools and support you need to be successful.
  • Flexible time off: We don’t count vacation days. When you need a break, take it — no strings attached.
  • Competitive pay: We offer strong salaries, performance bonuses, and equity opportunities for most roles.
  • Office and learning stipend: Get support for your growth with stipends for books, courses, and home office setup.
  • Global healthcare coverage: Medical, dental, and vision benefits are available in the US, Canada, India, and other supported countries.
  • Mental health and coaching support: Access professional coaching and mental health resources for you and your dependents.- Experience with 0 to 1 product initiatives is a plus, though not required
  • Experience in building and maintaining reliable analytics infrastructures
  • Strong experience in product analytics or a similar data-focused role, with a proven ability to impact product strategy and decision-making through data
  • Proficiency with data analytics tools and platforms (e.g., Looker, Amplitude) is a plus but not required. A focus on solving product challenges is more important than specific tool experience
  • Expertise in translating complex data into insights that are actionable for cross-functional teams
  • A high level of accountability, a passion for continuous learning, and the ability to thrive in a fast-paced, dynamic environment
  • Excellent communication skills, with the ability to clearly present data insights to both technical and non-technical stakeholders
  • Deep experience in working with exploratory analysis projects related to cohorting, time series analysis, and funnel analysis/optimization is required
  • Experience with Product Analytics tools to track end-to-end journeys/funnels (e.g., Amplitude, Heap, Mixpanel) and analyzing events within those products is essential
  • Proven ability to thrive in a fast-paced, dynamic startup environment with a high level of adaptability and a strong product sense, ensuring insights align with customer needs and product goals
  • Degree in Analytics, Applied Mathematics, Economics, Statistics, or related analytical field of study, or an equivalent combination of training and experience
  • Expert-level proficiency in influencing product strategy with SQL, A/B testing, machine learning, statistical analysis, and related tools like R, Python, SAS, etc., is required
  • Previous or current experience supporting SaaS (Product-Led Growth) companies with uncovering gaps and recalibrating activation metrics (e.g., aha/habit moments) is a huge plus

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