Walmart
Senior Manager, Data Science
As a Senior Manager, Data Science, you will lead a team of high-performing data scientists and analysts in delivering advanced analytical solutions that drive meaningful business decisions. This is a strategic, hands-on leadership role focused on end-to-end modeling, from exploratory data analysis to model deployment, visualization, and scaling. You will work closely with cross-functional partners to solve complex business problems using statistical modeling, machine learning, and AI. Your work will directly shape decision-making in product, marketing, finance, and operations, while mentoring the next generation of data leaders. This role is ideal for someone who thrives at the intersection of business impact, technical excellence, and team development. Deliver scalable, business-aligned analytical models. Lead the full lifecycle of advanced model development
from problem formulation and feature selection to algorithm choice, training, and validation. Apply advanced statistical and machine learning techniques including ensemble methods, NLP, and optimization to create robust models addressing key strategic objectives. Collaborate across business units to frame model goals within business context and establish relevant success metrics. Evaluate fit, robustness, and predictive accuracy using techniques such as ROC, RMSE, and A/B testing. Ensure models reflect business goals and scale effectively in production environments. Assess opportunities for AI to automate tuning and ongoing model improvement. Deploy, monitor, and scale models in production environments. Translate prototype models into production-ready code and workflows. Deploy and monitor model performance across diverse data environments, leveraging scalable infrastructure and robust logging practices. Regularly review model accuracy, parameter drift, and operational impact. Lead experimentation efforts and initiate iterative learning cycles to evolve models with changing data conditions. Work with engineering teams to ensure maintainability and resiliency of model APIs and pipelines. Visualize and communicate data-driven insights for actionable impact. Develop and refine sophisticated data visualizations using tools like Python (Matplotlib, Plotly), R (ggplot), Tableau, or PowerBI to effectively communicate model findings. Customize narrative structures and visual stories for executive audiences, technical teams, and stakeholders across the business. Present insights that align with business strategy, highlighting tradeoffs, confidence intervals, and potential impact. Guide junior team members in advanced storytelling practices and stakeholder communication strategies. Drive strategic alignment between data science and business outcomes. Leverage a deep understanding of business operations across domainssuch as finance, marketing, product, and operationsto identify opportunities where data science can drive transformational change. Act as a thought partner to business leaders, developing strategic data science roadmaps tied to measurable outcomes. Translate ambiguous business problems into clear analytical frameworks, ensuring alignment with strategic priorities. Coach, develop, and lead a high-impact data science team. Select, coach, and mentor a high-performing team of data scientists and analysts, fostering a culture of experimentation, ownership, and continuous learning. Establish clear performance goals tied to business outcomes, and regularly evaluate progress. Promote a sense of belonging and shared purpose, while advancing each team member's technical depth, business acumen, and leadership potential. Build a sustainable data strategy and ecosystem. Contribute to enterprise data strategy by helping define data access, governance, and tooling standards that align with long-term analytical goals. Evaluate and improve data quality and fitness-for-purpose by guiding teams on proper data source selection and ETL processes. Balance short-term delivery with long-term scalability by promoting reproducible workflows and sound documentation. Continuously evaluate and integrate AI to improve performance. Within the first 90180 days, take ownership of identifying how AI and automation tools can support or enhance the core responsibilities of this role. Proactively evaluate AI tools for tasks such as model retraining, anomaly detection, auto-ML, or bias monitoring. Collaborate with platform, MLOps, and product leaders to pilot AI-driven solutions that streamline experimentation, improve outcomes, and reduce manual effort. What You'll Bring
You bring proven experience building and deploying advanced machine learning models that drive real business outcomes at scale. You are fluent in Python or R and SQL, and comfortable with complex optimization, feature engineering, and production-level code. You are also a systems thinker who can connect modeling efforts with broader strategic goals. Your understanding of data infrastructure and deployment makes you a trusted technical leader. You've mentored data scientists, presented to C-level stakeholders, and helped shape team culture. Above all, you are driven by impact
using data to solve high-value problems, develop talent, and shape the future. To succeed in this role, you will have demonstrated: Ability to scope ambiguous problems, frame analytical approaches, and deliver practical solutions Mastery of statistical modeling, machine learning (Random Forests, SVM, Neural Networks), and modern AI techniques Deep experience with model validation and tuning techniques (ROC, RMSE, Chi-square, etc.) Expertise in data visualization and stakeholder storytelling, tailored for different audiences Strong leadership and coaching skills, with a track record of developing high-performing teams Business acumen across multiple domains (marketing, product, finance, HR), and fluency in key business metrics Experience deploying and scaling models in production environments, including monitoring and retraining Knowledge of data strategy, governance, and architecture A growth mindset and continuous learning ethos in a rapidly evolving field Minimum Qualifications
Option 1: Bachelors degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 5 years' experience in an analytics related field. Option 2: Masters degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 3 years' experience in an analytics related field. Option 3: 7 years' experience in an analytics or related field. Preferred Qualifications
Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Supervisory experience, Using open source frameworks (for example, scikit learn, tensorflow, torch), We value candidates with a background in creating inclusive digital experiences, demonstrating knowledge in implementing Web Content Accessibility Guidelines (WCAG) 2.2 AA standards, assistive technologies, and integrating digital accessibility seamlessly. The ideal candidate would have knowledge of accessibility best practices and join us as we continue to create accessible products and services following Walmart's accessibility standards and guidelines for supporting an inclusive culture. Primary Location
2101 Se Simple Savings Dr, Bentonville, AR 72712-4304, United States of America About Sam's Club
Sam Walton opened the first Sam's Club in 1983 to meet a growing need among customers who wanted to buy merchandise in bulk. Since then, Sam's Club has grown rapidly, opening more than 600 clubs in the U.S. and 100 clubs internationally. By offering affordable, wholesale merchandise to members, Sam's Club helps make saving simple for families and small business owners. Sam's Club employs about 110,000 associates in the U.S. The average club is 134,000 square feet and offers bulk groceries and general merchandise. Most clubs also have specialty services, such as a pharmacy, an optical department, a photo center, or a tire and battery center. Sam's Club is an Equal Opportunity Employer- By Choice. We believe we are best equipped to help our associates, customers, and the communities we serve live better when we really know them. That means understanding, respecting, and valuing unique styles, experiences, identities, abilities, ideas, and opinions- while being welcoming of all people.
As a Senior Manager, Data Science, you will lead a team of high-performing data scientists and analysts in delivering advanced analytical solutions that drive meaningful business decisions. This is a strategic, hands-on leadership role focused on end-to-end modeling, from exploratory data analysis to model deployment, visualization, and scaling. You will work closely with cross-functional partners to solve complex business problems using statistical modeling, machine learning, and AI. Your work will directly shape decision-making in product, marketing, finance, and operations, while mentoring the next generation of data leaders. This role is ideal for someone who thrives at the intersection of business impact, technical excellence, and team development. Deliver scalable, business-aligned analytical models. Lead the full lifecycle of advanced model development
from problem formulation and feature selection to algorithm choice, training, and validation. Apply advanced statistical and machine learning techniques including ensemble methods, NLP, and optimization to create robust models addressing key strategic objectives. Collaborate across business units to frame model goals within business context and establish relevant success metrics. Evaluate fit, robustness, and predictive accuracy using techniques such as ROC, RMSE, and A/B testing. Ensure models reflect business goals and scale effectively in production environments. Assess opportunities for AI to automate tuning and ongoing model improvement. Deploy, monitor, and scale models in production environments. Translate prototype models into production-ready code and workflows. Deploy and monitor model performance across diverse data environments, leveraging scalable infrastructure and robust logging practices. Regularly review model accuracy, parameter drift, and operational impact. Lead experimentation efforts and initiate iterative learning cycles to evolve models with changing data conditions. Work with engineering teams to ensure maintainability and resiliency of model APIs and pipelines. Visualize and communicate data-driven insights for actionable impact. Develop and refine sophisticated data visualizations using tools like Python (Matplotlib, Plotly), R (ggplot), Tableau, or PowerBI to effectively communicate model findings. Customize narrative structures and visual stories for executive audiences, technical teams, and stakeholders across the business. Present insights that align with business strategy, highlighting tradeoffs, confidence intervals, and potential impact. Guide junior team members in advanced storytelling practices and stakeholder communication strategies. Drive strategic alignment between data science and business outcomes. Leverage a deep understanding of business operations across domainssuch as finance, marketing, product, and operationsto identify opportunities where data science can drive transformational change. Act as a thought partner to business leaders, developing strategic data science roadmaps tied to measurable outcomes. Translate ambiguous business problems into clear analytical frameworks, ensuring alignment with strategic priorities. Coach, develop, and lead a high-impact data science team. Select, coach, and mentor a high-performing team of data scientists and analysts, fostering a culture of experimentation, ownership, and continuous learning. Establish clear performance goals tied to business outcomes, and regularly evaluate progress. Promote a sense of belonging and shared purpose, while advancing each team member's technical depth, business acumen, and leadership potential. Build a sustainable data strategy and ecosystem. Contribute to enterprise data strategy by helping define data access, governance, and tooling standards that align with long-term analytical goals. Evaluate and improve data quality and fitness-for-purpose by guiding teams on proper data source selection and ETL processes. Balance short-term delivery with long-term scalability by promoting reproducible workflows and sound documentation. Continuously evaluate and integrate AI to improve performance. Within the first 90180 days, take ownership of identifying how AI and automation tools can support or enhance the core responsibilities of this role. Proactively evaluate AI tools for tasks such as model retraining, anomaly detection, auto-ML, or bias monitoring. Collaborate with platform, MLOps, and product leaders to pilot AI-driven solutions that streamline experimentation, improve outcomes, and reduce manual effort. What You'll Bring
You bring proven experience building and deploying advanced machine learning models that drive real business outcomes at scale. You are fluent in Python or R and SQL, and comfortable with complex optimization, feature engineering, and production-level code. You are also a systems thinker who can connect modeling efforts with broader strategic goals. Your understanding of data infrastructure and deployment makes you a trusted technical leader. You've mentored data scientists, presented to C-level stakeholders, and helped shape team culture. Above all, you are driven by impact
using data to solve high-value problems, develop talent, and shape the future. To succeed in this role, you will have demonstrated: Ability to scope ambiguous problems, frame analytical approaches, and deliver practical solutions Mastery of statistical modeling, machine learning (Random Forests, SVM, Neural Networks), and modern AI techniques Deep experience with model validation and tuning techniques (ROC, RMSE, Chi-square, etc.) Expertise in data visualization and stakeholder storytelling, tailored for different audiences Strong leadership and coaching skills, with a track record of developing high-performing teams Business acumen across multiple domains (marketing, product, finance, HR), and fluency in key business metrics Experience deploying and scaling models in production environments, including monitoring and retraining Knowledge of data strategy, governance, and architecture A growth mindset and continuous learning ethos in a rapidly evolving field Minimum Qualifications
Option 1: Bachelors degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 5 years' experience in an analytics related field. Option 2: Masters degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 3 years' experience in an analytics related field. Option 3: 7 years' experience in an analytics or related field. Preferred Qualifications
Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Supervisory experience, Using open source frameworks (for example, scikit learn, tensorflow, torch), We value candidates with a background in creating inclusive digital experiences, demonstrating knowledge in implementing Web Content Accessibility Guidelines (WCAG) 2.2 AA standards, assistive technologies, and integrating digital accessibility seamlessly. The ideal candidate would have knowledge of accessibility best practices and join us as we continue to create accessible products and services following Walmart's accessibility standards and guidelines for supporting an inclusive culture. Primary Location
2101 Se Simple Savings Dr, Bentonville, AR 72712-4304, United States of America About Sam's Club
Sam Walton opened the first Sam's Club in 1983 to meet a growing need among customers who wanted to buy merchandise in bulk. Since then, Sam's Club has grown rapidly, opening more than 600 clubs in the U.S. and 100 clubs internationally. By offering affordable, wholesale merchandise to members, Sam's Club helps make saving simple for families and small business owners. Sam's Club employs about 110,000 associates in the U.S. The average club is 134,000 square feet and offers bulk groceries and general merchandise. Most clubs also have specialty services, such as a pharmacy, an optical department, a photo center, or a tire and battery center. Sam's Club is an Equal Opportunity Employer- By Choice. We believe we are best equipped to help our associates, customers, and the communities we serve live better when we really know them. That means understanding, respecting, and valuing unique styles, experiences, identities, abilities, ideas, and opinions- while being welcoming of all people.