(USA) Senior Manager, Data Analytics

Walmart•Bentonville, AR

1d•Onsite

About The Position

The Senior Manager, Data Analytics, leads the development and execution of data strategies that drive business insights and operational excellence. This role requires expertise in data sourcing, quality management, advanced analytics, and visualization to translate complex business challenges into actionable solutions. The position involves mentoring teams, collaborating cross-functionally, and ensuring alignment with organizational objectives. The successful candidate will apply analytical rigor and strategic thinking to enhance data-driven decision-making, promote continuous improvement, and support Walmart’s commitment to delivering measurable business value through innovative data practices. About the team: At Walmart Decision Sciences, the team tackles complex challenges that influence millions daily. Combining business insight with technical expertise, members include analysts, economists, data scientists, engineers, and product partners working collaboratively. The team focuses on building scalable solutions, starting with business needs and leveraging data, experimentation, and AI to enhance decision-making. Emphasizing continuous learning and value creation, the group drives improvements in customer understanding, operations, and supply chains. This environment supports solving impactful problems through clear communication and advanced analytical methods, fostering innovation and excellence in retail’s evolving landscape.

Requirements

Extensive experience in data analytics, including big data techniques and automation methods.
Proficiency in SQL, NoSQL, and data visualization tools such as Python libraries, Tableau, and PowerBI.
Strong understanding of data quality management, data governance, and enterprise data architecture principles.
Ability to translate complex business requirements into data-driven strategies and actionable insights.
Demonstrated leadership in mentoring teams and managing multiple projects with measurable business impact.
Excellent communication skills to influence stakeholders and present data-driven narratives effectively.
Knowledge of exploratory data analysis, statistical modeling, and data profiling techniques.
Bachelor's degree in Business, Engineering, Statistics, Economics, Analytics, Mathematics, Arts, Finance or related field and 4 years' experience in data analysis, data science, statistics, or related field.
Master's degree in Business, Engineering, Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 2 years' experience in data analysis, data science, statistics, or related field.
6 years' experience in data analysis, data science, statistics, or related field.
1 year's supervisory experience.

Nice To Haves

Data science, data analysis, statistics, or related field, Master’s degree in Business, Computer Science, Engineering, Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field
Related industry experience (for example, retail, merchandising, healthcare, eCommerce)
Successful completion of assessments in data analysis and Business Intelligence tools and scripting languages (for example, SQL, Python, Spark, Scala, R, Power BI, or Tableau)
Supervisory experience

Responsibilities

Identify and evaluate data sources aligned with business requirements and service level agreements to ensure data fitness for purpose.
Translate complex business problems into data-driven solutions using advanced analytics and automation techniques.
Design and implement data visualizations that effectively communicate insights and support decision-making across stakeholders.
Develop and execute data quality management processes, including profiling, cleansing, and monitoring to maintain high data standards.
Lead data strategy initiatives that optimize data accessibility, governance, and monetization aligned with enterprise objectives.
Mentor team members on analytics methodologies, visualization best practices, and business context integration.
Collaborate cross-functionally to align analytics efforts with business goals and drive continuous improvement.