Senior/Principal Data Scientist, Product Analytics at Gallup, Inc-Usa

San Francisco, California, United States -

Full Time

Start Date

Immediate

Expiry Date

28 May, 26

Salary

235000.0

Posted On

27 Feb, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

SQL, Python, Data Science, Product Analytics, Experimentation, A/B Testing, Data Modeling, Dashboarding, Statistical Intuition, Data Storytelling, Hypothesis Validation, Instrumentation, Snowflake, Redshift, AI

Industry

Business Consulting and Services

Description

Shape product road maps and strategies with data-driven analytics and insights. As a senior/principal data scientist focused on product analytics for our Technology team, you’ll work with product managers, engineers and designers to define success, validate hypotheses, and measure user behavior and product performance. We’re looking for self-driven, curious analytics partners who thrive in ambiguity, learn continually and help teams accelerate decision-making. At Gallup, our analytics reflect what the world is thinking, empower millions of people to thrive using their strengths, and help leaders create exceptional workplaces. If you want your work to influence products that bring that mission to life, we’d love to hear from you. What You’ll Do Partner with product teams early in discovery, road map discussions and launch planning to turn goals into measurable outcomes Define and govern success metrics by building trusted metric definitions, dashboards and data models that enable self-serve decision-making Design and evaluate product experiments and analyses to assess the impact of new features, onboarding changes and product improvements Serve as a thought partner to product managers by pressure-testing hypotheses before implementation and confirming whether outcomes match expectations after launch Translate analysis into action by communicating what happened; why it happened; and what stakeholders, leaders and partners should do next Improve analytics readiness by partnering with data platform and engineering teams on instrumentation, extraction, processing and modeling to ensure reliable, analysis-ready data Scale product analytics at Gallup by contributing to best practices, frameworks and repeatable ways of working What Makes You Stand Out Proactive problem-solving: You anticipate issues and opportunities in the data, translate analysis into action, and rapidly drive improvements to the user experience. Persistent resourcefulness: You independently create clarity from ambiguity, connecting distributed data, validating quality and delivering insights without relying on fully defined systems. Trusted product partnership: You collaborate closely with product, engineering, design, research and operations teams to solve complex problems, and confidently deliver constructive, data-backed recommendations. Experimentation judgment: You know when A/B tests are feasible and when they aren’t, and you can choose rigorous alternatives to answer product questions. Expert data storytelling: You explain trends, uncertainty and limitations in plain language and deliver recommendations people can act on. Curious culture-builder: You experiment with emerging tools, including AI, to improve team effectiveness and actively build data fluency so partners can confidently navigate metrics and insights. What You Need Bachelor’s degree in computer science, computer engineering, mathematics, statistics or a related field, or equivalent experience, required At least five years of experience in product analytics or data science required; eight or more years of experience preferred At least five years of experience with SQL for analysis in modern data environments required At least five years of experience with Python and data science tool kits (e.g., pandas) required Experience leading data-driven projects end to end, including defining metrics, designing experiments/analyses and communicating actionable insights required Strong statistical intuition, analytical rigor, and experience validating data and performing quality checks required High fluency with MPP databases such as Snowflake or Redshift required Some data engineering or instrumentation experience (pipelines, event tracking, modeling) preferred A commitment to working on-site at Gallup’s San Francisco office at least three days per week required About Gallup At Gallup, we change the world, one client at a time, through extraordinary analytics and advice on everything important facing humankind. Learn more about our work and life at Gallup. Gallup offers a robust benefits package that includes medical, dental, vision, life and other insurance options; a fully vested 401(k) retirement savings plan with company matching; an employee stock ownership program; mass transit reimbursement; family-building benefits; an employee assistance program; and various reimbursements and activities that enhance our associates’ wellbeing. We also offer an estimated annual salary range of $175,000-$235,000 for this role. Salaries are based on a variety of factors, including an individual’s education, experience and skills. Gallup is an equal opportunity employer. We consider all qualified applicants without regard to race, color, religion, sex, national origin, disability, protected veteran status, sexual orientation, gender identity, or any other legally protected basis, in accordance with applicable law. To review Gallup’s Privacy Statement, please click this link: https://www.gallup.com/privacy. This privacy policy is meant to help you understand what information we collect, why we collect it, and how you can update, manage and delete your information. Your application and the information you provide will be processed and stored in the United States. #LI-Hybrid #LI-KW1

How To Apply:

Incase you would like to apply to this job directly from the source, please click here

Responsibilities

The role involves partnering with product teams to define success metrics, build trusted data models and dashboards, and design/evaluate product experiments to assess feature impact. You will translate analysis into actionable recommendations for stakeholders and improve analytics readiness by collaborating with engineering on data infrastructure.