Data Scientist Associate

We at Best Buy work hard every day to enrich the lives of customers through technology, whether they come to us online, visit our stores, or invite us into their homes. We do this by solving technology problems and addressing key human needs across a range of areas, including entertainment, productivity, communicating with coworkers and loved ones, preparing nutritious food, providing security for your home and family, and helping you take your health to the next level.

• Collect, clean, and preprocess large-scale datasets from Big Query, Teradata, and other sources to create reliable features.
• Develop hypotheses and conduct exploratory data analysis to discover key predictors and drivers of workforce outcomes.
• Design, train, validate, and optimize forecasting, scheduling, and labor cost models balancing productivity and fairness metrics.
• Conduct rigorous experimentation and causal analysis (A/B testing) to evaluate labor interventions’ impact on sales and employee satisfaction.
• Build and maintain dashboards and reports tracking labor KPIs and model performance.
• Partner with MLOps teams to prepare models for deployment, ensure version control, enable experiment logging, and implement performance monitoring and incident response protocols.
• Communicate complex model designs, assumptions, and business impact effectively to stakeholders to support data-driven labor planning and decisions.

• This position is not eligible for immigration sponsorship.
• Bachelor’s degree in a quantitative field (Data Science, Statistics, Computer Science, Engineering, Mathematics, Operations Research, etc.).
• 2+ years of relevant professional experience in analytics, data science, or a closely related field (or equivalent experience).
• 2+ years of experience using Python and SQL (e.g., Big Query, Teradata) for data wrangling, analysis, and modeling, including hands‑on use of core data science libraries such as Num Py, Pandas, Sci Py, scikit‑learn, and stats models.
• 2+ years of experience applying statistics, data analysis, and quantitative modeling to diverse business problems; able to design, validate, and clearly communicate predictive, prescriptive, and descriptive models.
• 2+ years of working knowledge of mathematical optimization and operations research; able to formulate and solve decision-making problems (e.g., resource allocation, scheduling, task assignment, inventory, routing) by translating business constraints into mathematical models.
• 2+ years of experience with time‑series forecasting methods and libraries (e.g., Prophet, stats models) and applying them to real business use cases.
• 2+ years of experience with Git/Git Hub or similar version‑control systems for collaborative development, code review, and reproducibility.
• 1+ year of experience with cloud ML pipeline orchestration (e.g., Kubeflow on GCP), including CI/CD, artifact and metadata tracking, monitoring execution, and logging model/system metrics.
• 1+ years of experience with Bash or other shell scripting for workflow automation and data pipelines.

• Advanced experience with Python data manipulation and distributed computing libraries such as Polars and Dask. Proficiency with machine learning frameworks beyond the core stack, including XGBoost, Light
  
  GBM, Cat Boost, PyTorch, and Tensor Flow/Keras.
• Strong grounding in advanced statistical and time-series techniques, including hypothesis testing, ANOVA, ARIMA/SARIMA, ETS, bootstrapping, and regression diagnostics.
• Expertise in mathematical optimization using solvers such as Gurobi, OR‑Tools, PuLP, Pyomo, and CPLEX, with strong knowledge of linear programming, mixed‑integer programming (MIP), and duality theory.
• Deep domain knowledge of retail, workforce, and supply chain operations.
• Experience with Google Cloud Platform tools including Vertex AI for managing the end-to-end machine learning lifecycle (data preparation, model training, hyperparameter tuning, deployment, and monitoring); familiar with Vertex AI Workbench, AutoML for automated model building, Vertex AI Pipelines for workflow orchestration, Model Registry for managing models, and integration with Big Query and…