Senior Product Analyst

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Analyzing product data to support PlayStation's future. Collaborating with teams for data-driven insights and decision-making.

Work closely with product feature teams to understand their roadmap and translate initiative goals into data KPIs, targets, and measurement plans.
Extract and integrate data from various sources to support analytical efforts, coordinating with data product, engineering, data science, and other analytics teams as needed.
Lead A/B test experiments, validate test data, monitor progress, perform post-test analysis, and provide recommendations for feature release decisions, collaborating with the experimentation platform team as necessary.
Convert business questions into data analytics tasks, conduct thorough analyses to segment and explore data, identify key drivers, and generate actionable insights to inform business decisions.
Collaborate with data scientists on research and innovation, applying standardized processes and enhancing analytics methodologies as they become available. Contribute to the development and use of digital tools, reporting visualization, and analytical storytelling.
Work with the reporting team to define and create automated and self-serve dashboards, providing relevant information efficiently to optimize business operations and track key initiatives.

Bachelor’s Degree in Statistics, Mathematics, Analytics, Data Science, Business, Economics, or a related field, with 3+ years of relevant professional experience in data analysis. A related Master’s Degree is a plus.
Experience working with product, business, or other partner teams, including conducting experiments and supporting optimization efforts such as A/B testing, holdout groups, and multivariate analysis is a must. Familiarity with quasi-experimental causal inference methodologies is a plus.
Relevant experience in data analysis with advanced SQL, Python/ R skills is required; Experience with user journey tools (e.g., Adobe Analytics) and standard BI tools (e.g., MicroStrategy, Tableau, Domo) is highly preferred.
Strong understanding of statistical concepts (e.g., confidence intervals, hypothesis testing) and analytic modeling techniques (e.g., multivariate/linear regression, k-means clustering) is preferred.
Excellent written and verbal communication skills, with experience presenting analytical results to non-technical partners.