Data Scientist III Surveys/Longitudinal Data Scientist

Data Scientist III

Los Angeles, CA (Hybrid)

Contract- 12 months

Responsibilities:

• Work as part of a central team to build insights and frameworks that improve Client foundational understanding of our players and games
• Create and test hypotheses about the ways sentiment and engagement / monetization interrelate, including exploration of both leading and lagging relationships
• Conduct exploratory data analysis and build models that connect complex sentiment with player telemetry data, for the same subjects
• Transform and prepare datasets, including longitudinal survey and other complex datasets, to be amenable to the above analyses
• Consult on survey design and methodology, to improve the chance of success with the above analyses
• Partner with analysts and researchers to generate documentation of your findings
• Improve the state of various data science products within the remit of Central Product Insights, including feature additions, product maintenance, and automation
• Train analysts and data scientists to re-run your analyses and work with any models or other data science products that you build / improve

Required Qualifications

• D. in Machine Learning, AI, Statistics, Math, or related Computer Science/Quantitative field with 3+ years of industry experience (including Postdoc), or equivalent experience (i.e., M.S. with 4-6+ years of relevant experience, or B.S. with 6-8+ years of relevant experience)
• Proficiency using Python and SQL for large-scale data analysis in distributed computing environments (e.g., Spark or cloud-based platforms like Databricks)
• Experience conducting exploratory data analysis on ordinal and continuous data, with a focus on extracting meaningful insights to inform hypotheses, models, or product decisions.
• Proficiency applying causal inference methods to observational panel data (e.g., fixed effects, inverse probability weighting).
• Experience modeling longitudinal sentiment data, especially multi-item constructs (e.g., using latent growth models or hierarchical models).
• Skilled in preparing complex survey datasets, including handling multicollinearity, missing data, irregular time spacing, weighting, and reshaping wide/long data.
• Familiarity with survey methodology and longitudinal study design, including:
  • Wave cadence and timing
  • Panel attrition and bias mitigation strategies
  • Question construction and psychometric consistency

Desired Qualifications

• Prior experience working with player-facing survey programs.
• Prior experience working with researcher tools for survey analysis (e.g., R, Q, SPSS).
• Strong communication and documentation skills for sharing insights with cross-functional partners.