Best Buy
Data Scientist Associate
Best Buy is a vibrant technology company that helps customers across multiple channels—online, in store, and at home—to access innovative products and services.
As a Data Scientist Associate, you will drive changes for the Workforce business team, impact our labor strategy, and add value through innovative data capabilities and insights to optimize our labor planning.
Base Pay Range $80,070.00/yr – $143,208.00/yr
What You’ll Do
Collect, clean, and preprocess large‑scale datasets from BigQuery, 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.
Basic Qualifications
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., BigQuery, Teradata) for data wrangling, analysis, and modeling, including hands‑on use of core data science libraries such as NumPy, Pandas, SciPy, scikit‑learn, and statsmodels.
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, statsmodels) and applying them to real business use cases.
2+ years of experience with Git/GitHub 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.
Preferred Qualifications
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, LightGBM, CatBoost, PyTorch, and TensorFlow/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; familiarity with Vertex AI Workbench, AutoML, Vertex AI Pipelines, Model Registry, and integration with BigQuery and Cloud Storage.
Proficiency in Business intelligence tools: Power BI, Looker, Looker Studio.
Backend API development: FastAPI, Flask for prediction and optimization services integrated with operational tools.
Master's degree in a quantitative field (Data Science, Statistics, Computer Science, Engineering, Math, Operations Research, etc.).
Benefits
Competitive pay
Generous employee discount
Physical and mental well‑being support
About Us As part of the Best Buy team, you’ll help us fulfill our purpose to enrich lives through technology.
We bring that to life every day by humanizing and personalizing tech solutions for every stage of life—whether in our stores, online, or in customers’ homes.
Our culture is built on deeply supporting and valuing our amazing employees, creating a great place to work where you can unlock unique career possibilities and bring your full, authentic self to work now and into the future.
Best Buy is an equal opportunity employer.
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As a Data Scientist Associate, you will drive changes for the Workforce business team, impact our labor strategy, and add value through innovative data capabilities and insights to optimize our labor planning.
Base Pay Range $80,070.00/yr – $143,208.00/yr
What You’ll Do
Collect, clean, and preprocess large‑scale datasets from BigQuery, 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.
Basic Qualifications
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., BigQuery, Teradata) for data wrangling, analysis, and modeling, including hands‑on use of core data science libraries such as NumPy, Pandas, SciPy, scikit‑learn, and statsmodels.
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, statsmodels) and applying them to real business use cases.
2+ years of experience with Git/GitHub 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.
Preferred Qualifications
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, LightGBM, CatBoost, PyTorch, and TensorFlow/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; familiarity with Vertex AI Workbench, AutoML, Vertex AI Pipelines, Model Registry, and integration with BigQuery and Cloud Storage.
Proficiency in Business intelligence tools: Power BI, Looker, Looker Studio.
Backend API development: FastAPI, Flask for prediction and optimization services integrated with operational tools.
Master's degree in a quantitative field (Data Science, Statistics, Computer Science, Engineering, Math, Operations Research, etc.).
Benefits
Competitive pay
Generous employee discount
Physical and mental well‑being support
About Us As part of the Best Buy team, you’ll help us fulfill our purpose to enrich lives through technology.
We bring that to life every day by humanizing and personalizing tech solutions for every stage of life—whether in our stores, online, or in customers’ homes.
Our culture is built on deeply supporting and valuing our amazing employees, creating a great place to work where you can unlock unique career possibilities and bring your full, authentic self to work now and into the future.
Best Buy is an equal opportunity employer.
#J-18808-Ljbffr