Senior Data Scientist in Grapevine, TX at GameStop

Date Posted: 7/28/2021

Job Snapshot

Job Description



Under general supervision, the Senior Data Scientist works collaboratively with others to develop, design, and implement statistical models to improve GameStop’s new, used, and trade-in business model.  This position utilizes extensive knowledge of statistical programs to drive modeling initiatives with innovation and provide results and recommendations to management using non-statistical language. The role will identify the factors that shape key trends, areas of opportunity, and insights into customer behavior and related areas. This position will provide In-depth data analysis and model formulations in response to business needs. Application of complex and simple statistical and machine learning tools to summarize data in information and vision, in terms of business models, describes the key role of the position. Associates in the role will mentor and guide junior statisticians and data scientists in data science process, procedures, and methodologies.


  • Customer Profiles/Segmentation: Evaluate characteristics across multiple dimensions such as demographic, behavior and product usage
  • Personalization: Implementing statistical models and machine learning algorithms to optimize for customer and business outcomes at scale
  • Targeting: Building predictive response models to choose best outcome to support the customer
  • Test design: Build statistical measurement capabilities to measure incremental impact of new experiences on a wide variety of outcomes
  • Applying our expertise in quantitative analysis, data mining and presentation of data to see beyond the numbers and understand how our users interact with our core/business products.
  • Partnering with Customer Support, Research, Product Specialist, Community, Social and Engineering teams to identify trends and opportunities
  • Informing, influencing, and supporting our product decisions using insight on customer contact and feedback
  • Designing and evaluating experiments monitoring key metrics, understanding root cause of changes in metrics
  • Building and analyzing dashboards and reports
  • Understanding the customer support ecosystems, user behaviors, and long-term trends
  • Identify levers to help move key metrics
  • Evaluating and identifying metrics
  • Building models of user behaviors for analysis


  • Collaboration – works effectively and cooperatively with others, establishing and maintaining good working relationships.
  • Information Monitoring – Establishes ongoing procedures to collect and review information needed to manage ongoing activities within an organization; monitors existing information sources for discrepancies or optimal information retrieval.
  • Operational Decision Making - Securing and comparing information from multiple sources to identify business issues, committing to an action after weighing alternative solutions against important decision criteria. Recognizes issues, problems, or opportunities and determines whether action is needed.
  • Planning and Organizing - Establishes courses of action for self to ensure that work is completed efficiently; proactively recognizes the need for innovation or improvement and initiates efforts to explore alternative solutions.


  • Accredited bachelor’s degree in accounting, finance, or business administration required; equivalent work experience may be considered as a substitution.  Master’s degree preferred.
  • 8+ years’ experience conducting quantitate analysis
  • 6+ years of Data Analyst experience on consumer facing web and/or mobile applications
  • 3+ Years of experience utilizing tools like Tableau, R, Excel, etc.


  • Proficient knowledge of data, charts, analysis, trends, and evangelizing data usage
  • Proficient database and querying skills including SQL
  • Expert ability to work with statistical packages such as SAS, R, MATLAB, SPSS, and Strata etc.
  • Expert ability to work with big data and its query and statistical tolls in Hadoop, Teradata, Vertica
  • Proficient Linux skills (shell scripting, Python, Java, PHP, etc.)
  • Expert skills in statistical concepts including regression analysis, time series models (including ARIMA and smoothing methods), Logit and Probit models, Multinomial logit, mixed model, incremental models, simultaneous equations, nonparametric regression and Bayesian statistics, decision tree with CHAID models, clustering techniques, simulations, and Monte-Carlo method
  • Proficient ability to work with in marketing algorithms including propensity and churn models, survival analysis, customer’s lifetime valuation, circle of life modelling, RFM models, K-Means clustering, Marketing Mixed modeling

Presentation skills including creating Keynote/PowerPoint presentations