Senior Data Scientist - Product
New
J
JobgetherProduct Analytics
United StatesFull-TimeSenior
SalaryTier 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.
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Job Details
- Required Skills
- PythonSQLMachine LearningA/B testingR
Requirements
- Bachelor’s degree in Analytics, Applied Mathematics, Economics, Statistics, or another relevant analytical discipline.
- Strong professional experience in product analytics, data science, or a closely related data-focused role.
- 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.
- Strong ability to transform complex quantitative findings into clear, practical recommendations.
- Strong product sense, business judgment, accountability, adaptability, and a continuous-learning mindset.
Responsibilities
- 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.
- Communicate findings clearly through recommendations, presentations, and reports tailored to both technical and non-technical audiences.
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