Senior Data Scientist - Product

Accountabilities:

• • Translate business and product needs into rigorous analyses, actionable insights, and recommendations that improve product performance and user experience.
  • Partner with product managers, engineers, and cross-functional stakeholders to identify critical questions, frame analytical approaches, and guide data-informed decisions.
  • Conduct exploratory and advanced analyses, including cohorting, time-series analysis, funnel analysis, experimentation, statistical analysis, and machine learning where appropriate.
  • Build, maintain, and improve scalable analytics infrastructure, ensuring data collection, reporting, and analytical outputs are reliable, accurate, and fit for purpose.
  • Establish and promote best practices for data analysis, measurement, reporting, and interpretation across product teams.
  • Identify opportunities to improve activation, engagement, conversion, and other key product outcomes, translating findings into practical initiatives.
  • Support product optimization as well as selected 0-to-1 launches by defining meaningful metrics and analyzing early-stage product performance.
  • Use SQL, Python, R, SAS, and related analytical tools to investigate complex product questions and influence product strategy.
  • Work with product analytics platforms and event data to understand end-to-end user journeys, funnels, and behavioral patterns.
  • Communicate findings clearly through recommendations, presentations, and reports tailored to both technical and non-technical audiences.
  • Promote a culture of data-driven decision-making, continuous experimentation, and measurable product improvement.
  • Take ownership of analytical projects from problem definition through execution, recommendation, and measurement of impact.

  Requirements:

  • Bachelor’s degree in Analytics, Applied Mathematics, Economics, Statistics, or another relevant analytical discipline, or an equivalent combination of education and professional experience.
  • Strong professional experience in product analytics, data science, or a closely related data-focused role, with demonstrated influence on product strategy and decision-making.
  • Deep hands-on experience with exploratory analysis involving cohorting, time-series analysis, funnel analysis, and product optimization.
  • Expert-level proficiency in SQL, A/B testing, statistical analysis, machine learning, and analytical programming languages such as Python, R, or SAS.
  • Experience building and maintaining dependable analytics infrastructure and ensuring the quality and integrity of data used for decision-making.
  • Experience with product analytics platforms such as Amplitude, Heap, or Mixpanel and the ability to analyze event-level data and end-to-end customer journeys.
  • Strong ability to transform complex quantitative findings into clear, practical recommendations that cross-functional teams can act upon.
  • Experience supporting SaaS or product-led growth environments is highly valuable, particularly around activation metrics, user journeys, and identifying opportunities to improve product adoption.
  • Exposure to 0-to-1 product development and early-stage product measurement is a plus.
  • Excellent communication and presentation skills, with the ability to influence both technical and business stakeholders.
  • Strong product sense, business judgment, accountability, adaptability, and a continuous-learning mindset.
  • Comfortable operating in a fast-moving environment where priorities evolve and analytical decisions may need to be made with imperfect information.

  Benefits:

  • Competitive total cash compensation, with annual base salary and bonus considerations.
  • Tier 1 salary range: $160,000–$200,000 USD for San Francisco, New York City, and Seattle.
  • Tier 2 salary range: $140,000–$176,000 USD for other U.S. locations.
  • Equity opportunities.
  • 401(k) plan.
  • At least 10 paid holidays per year.
  • Flexible paid time off and parental leave.
  • Medical, dental, and vision coverage.
  • FSA/HSA options.
  • Life, AD&D, short-term disability, and long-term disability insurance.
  • Employee assistance and wellbeing programs.
  • Global travel coverage.
  • Opportunities for professional growth, autonomy, experimentation, and meaningful product impact.
  • Remote work environment with a strong emphasis on ownership, collaboration, continuous improvement, and the use of AI and automation to work more effectively.