Walmart
Principal, Data Scientist/Economist - Workforce In...
Walmart, Bentonville, Arkansas, United States, 72712
Principal Data Scientist Economist - Workforce Intelligence - Insights
Walmart sells hundreds of billions of dollars a year in merchandise, manages thousands of stores, clubs, and distribution centers, and employs over two million people worldwide. Our Global People function is critical to managing this vast workforce effectively. Walmarts scale and complexity necessitate careful, sophisticated analysis. The Walmart Workforce Intelligence and Insights organization is responsible for leveraging data-driven insights to optimize our human capital strategies and enhance employee experiences while driving business outcomes. The team aims to understand the dynamics of our workforce, improve employee engagement, and drive organizational performance. As a Principal Data Scientist on this team, you will work on projects that provide critical insights into employee behavior, performance, and engagement, directly influencing strategic decisions and organizational outcomes. We are seeking a candidate with experience in econometrics, causal inference, and AI to uncover deep insights about our workforce, collaborate on the development of key tools and data platforms, and drive strategic decision-making. Code Development and Testing: Requires knowledge of coding languages like SQL, Java, C++, Python and others; Testing methods such as static, dynamic, software composition analysis, manual penetration testing and others; Business, domain understanding. To write code to develop the required solution and application features by determining the appropriate programming language and leveraging business, technical, and data requirements. Create test cases to review and validate the proposed solution design. Create proofs of concept. Test the code using the appropriate testing approach. Deploy software to production servers. Contribute code documentation, maintain playbooks, and provide timely progress updates. Tech. Problem Formulation: Requires knowledge of Analytics/big data analytics / automation techniques and methods; Business understanding; Precedence and use cases; Business requirements and insights. To analyze the business problem within one's discipline and questions assumptions to help the business identify the root cause. Identify and recommend approach to resolve the business problem to create effective technology focused solutions. Set relevant deliverables based on the established success criteria and define key metrics to measure progress and effectiveness of the solution. Quantify business impact. Data Source Identification: Requires knowledge of Functional business domain and scenarios; Categories of data and where it is held; Business data requirements; Database technologies and distributed datastores (e.g. SQL, NoSQL); Data Quality; Existing business systems and processes, including the key drivers and measures of success. To understand the priority order of requirements and service level agreements. Define and identify the most suitable sources for required data that is fit for purpose, referring to external sources as required. Perform initial data quality checks on the extracted data. Review the deliverables of junior associates and provides guidance on data source and quality. Data Strategy: Requires knowledge of understanding of business value and relevance of data and data enabled insights / decisions; Appropriate application and understanding of data ecosystem including Data Management, Data Quality Standards and Data Governance, Accessibility, Storage and Scalability, etc.; Understanding of the methods and applications that unlock the monetary value of data assets. To understand, articulate, interpret, and apply the principles of the defined strategy to unique, moderately complex business problems that may span one or more functions or domains. Understanding Business Context: Requires knowledge of Industry and environmental factors; Common business vernacular; Business practices across two or more domains such as product, finance, marketing, sales, technology, business systems, and human resources and in-depth knowledge of related practices; Directly relevant business metrics and business areas. To evaluate proposed business cases for projects and initiatives. Translate business requirements into strategies, initiatives, and projects and aligns them to business strategy and objectives, and drives the execution of deliverables. Build and articulate the business case and return on investment and delivers work that has demonstrable value. Challenge business assumptions on topics related to one's domain expertise. Mentor the team members on new business insights and allied developments. Proactively engage in the external community to build Walmart's brand and learn more about industry practices. Data Visualization: Requires knowledge of Visualization guidelines and best practices for complex data types; Multiple data visualization tools (for example, Python, R libraries, GGplot, Matplotlib, Ploty, Tableau, PowerBI etc.); Advanced visualization techniques/ tools; Multiple story plots and structures (OABCDE); Communication & influencing technique; Emotional intelligence. To identify and recommend the most suitable visualization tools based on context. Generate appropriate graphical representations of data and model outcomes. Understand customer requirements to design appropriate data representation for complex data sets and drive User Experience designers and User Interface engineers to build front end applications. Define application design based on customer requirements. Build compelling stories based on context to integrate multiple pieces of information into cohesive insights. Present to and influence audiences using the appropriate data visualization frameworks and conveys clear messages through deep business and stakeholder understanding. Customize communication style based on stakeholders and leverages relationships to drive behavioral change. Guide and mentor junior associates on story types, structures, and techniques based on context. Analytical Modeling: Requires knowledge of feature relevance and selection; Exploratory data analysis methods and techniques; Advanced statistical methods and best-practice advanced modelling techniques (e.g., graphical models, Bayesian inference, basic level of NLP, Vision, neural networks, SVM, Random Forest etc.); Multivariate calculus; Statistical models behind standard ML models; Advanced excel techniques and Programming languages like R/Python; Basic classical optimization techniques (e.g., Newton-Rapson methods, Gradient descent); Numerical methods of optimization (e.g. Linear Programming, Integer Programming, Quadratic Programming, etc.) To select appropriate modeling techniques for complex problems with large scale, multiple structured and unstructured data sets. Select and develop variables and features iteratively based on model responses in collaboration with the business. Conducts exploratory data analysis activities (for example, basic statistical analysis, hypothesis testing, statistical inferences) on available data. Identify dimensions and designs of experiments and create test and learn frameworks. Interpret data to identify trends to go across future data sets. Create continuous, online model learning along with iterative model enhancements. Develop newer techniques (for example, advanced machine learning algorithms, auto ML) by leveraging the latest trends in machine learning, artificial intelligence to train algorithms to apply models to new data sets. Guide the team on feature engineering, experimentation, and advanced modeling techniques to be used for complex problems with unstructured and multiple data sets (for example, streaming data, raw text data). Model Assessment and Validation: Requires knowledge of model fit testing, tuning, and validation techniques (e.g., Chi square, ROC curve, root mean square error etc.); Impact of variables and features on model performance To identify and review model evaluation metrics based on analytical requirements. Apply suitable techniques for model testing and tuning, to assess accuracy, fit, validity, and robustness. Ensure testing information is documented and maintained by the team. Model Deployment and Scaling: Requires knowledge of impact of variables and features on model performance; understanding of servers, model formats to store models. To deploy models or model ensemble and ensure sustainability and maintenance overtime. Implement model monitoring and model life-cycle management practices. Assist in creation of innovative user interfaces and support the use of models through collaboration with key stakeholders. Drives the execution of multiple business plans and projects by identifying customer and operational needs; developing and communicating business plans and priorities; removing barriers and obstacles that impact performance; providing resources; identifying performance standards; measuring progress and adjusting performance accordingly; developing contingency plans; and demonstrating adaptability and supporting continuous learning. Provides supervision and development opportunities for associates by selecting and training; mentoring; assigning duties; building a team-based work environment; establishing performance expectations and conducting regular performance evaluations; providing recognition and rewards; coaching for success and improvement; and fosters a culture of belonging. Promotes and supports company policies, procedures, mission, values, and standards of ethics and integrity by training and providing direction to others in their use and application; ensuring compliance with them; and utilizing and supporting the Open Door Policy. Ensures business needs are being met by evaluating the ongoing effectiveness of current plans, programs, and initiatives; consulting with business partners, managers, co-workers, or other key stakeholders; soliciting, evaluating, and applying suggestions for improving efficiency and costeffectiveness; and participating in and supporting community outreach events. Leadership Expectations Respect for the Individual: Demonstrates and encourages respect for all; builds a high-performing, team; seeks, and embraces differences in people, cultures, ideas and experiences; creates a workplace and equitable experiences where associates feel seen, supported and connected through culture of belonging so associates thrive and perform; drives a positive associate and customer/member experience for all; identifies, attracts, and retains the best, team members. Respect for the Individual: Creates a discipline and focus around developing talent, through feedback, coaching, mentoring, and developmental opportunities; promotes an environment allowing everyone to bring their best selves to work; empowers associates and partners to act in the best interest of the customer/member and company; and regularly recognizes others contributions and accomplishments. Respect for the Individual: Builds strong and trusting relationships with team members and business partners; works collaboratively and cross-functionally to achieve objectives; and communicates and listens attentively, with energy and positivity to motivate, influence, and inspire commitment and action. Acts with Integrity: Maintains and promotes the highest standards of integrity, ethics and compliance; models the Walmart values and leads by example to foster our culture;supports Walmarts goal of becoming a regenerative company by making a positive impact for associates, customers, members, and the world around us. Acts with Integrity: Follows the law, our code of conduct and company policies, and sets expectations for others to do the same; promotes an environment where associates feel comfortable sharing concerns and reinforces our culture of non
Walmart sells hundreds of billions of dollars a year in merchandise, manages thousands of stores, clubs, and distribution centers, and employs over two million people worldwide. Our Global People function is critical to managing this vast workforce effectively. Walmarts scale and complexity necessitate careful, sophisticated analysis. The Walmart Workforce Intelligence and Insights organization is responsible for leveraging data-driven insights to optimize our human capital strategies and enhance employee experiences while driving business outcomes. The team aims to understand the dynamics of our workforce, improve employee engagement, and drive organizational performance. As a Principal Data Scientist on this team, you will work on projects that provide critical insights into employee behavior, performance, and engagement, directly influencing strategic decisions and organizational outcomes. We are seeking a candidate with experience in econometrics, causal inference, and AI to uncover deep insights about our workforce, collaborate on the development of key tools and data platforms, and drive strategic decision-making. Code Development and Testing: Requires knowledge of coding languages like SQL, Java, C++, Python and others; Testing methods such as static, dynamic, software composition analysis, manual penetration testing and others; Business, domain understanding. To write code to develop the required solution and application features by determining the appropriate programming language and leveraging business, technical, and data requirements. Create test cases to review and validate the proposed solution design. Create proofs of concept. Test the code using the appropriate testing approach. Deploy software to production servers. Contribute code documentation, maintain playbooks, and provide timely progress updates. Tech. Problem Formulation: Requires knowledge of Analytics/big data analytics / automation techniques and methods; Business understanding; Precedence and use cases; Business requirements and insights. To analyze the business problem within one's discipline and questions assumptions to help the business identify the root cause. Identify and recommend approach to resolve the business problem to create effective technology focused solutions. Set relevant deliverables based on the established success criteria and define key metrics to measure progress and effectiveness of the solution. Quantify business impact. Data Source Identification: Requires knowledge of Functional business domain and scenarios; Categories of data and where it is held; Business data requirements; Database technologies and distributed datastores (e.g. SQL, NoSQL); Data Quality; Existing business systems and processes, including the key drivers and measures of success. To understand the priority order of requirements and service level agreements. Define and identify the most suitable sources for required data that is fit for purpose, referring to external sources as required. Perform initial data quality checks on the extracted data. Review the deliverables of junior associates and provides guidance on data source and quality. Data Strategy: Requires knowledge of understanding of business value and relevance of data and data enabled insights / decisions; Appropriate application and understanding of data ecosystem including Data Management, Data Quality Standards and Data Governance, Accessibility, Storage and Scalability, etc.; Understanding of the methods and applications that unlock the monetary value of data assets. To understand, articulate, interpret, and apply the principles of the defined strategy to unique, moderately complex business problems that may span one or more functions or domains. Understanding Business Context: Requires knowledge of Industry and environmental factors; Common business vernacular; Business practices across two or more domains such as product, finance, marketing, sales, technology, business systems, and human resources and in-depth knowledge of related practices; Directly relevant business metrics and business areas. To evaluate proposed business cases for projects and initiatives. Translate business requirements into strategies, initiatives, and projects and aligns them to business strategy and objectives, and drives the execution of deliverables. Build and articulate the business case and return on investment and delivers work that has demonstrable value. Challenge business assumptions on topics related to one's domain expertise. Mentor the team members on new business insights and allied developments. Proactively engage in the external community to build Walmart's brand and learn more about industry practices. Data Visualization: Requires knowledge of Visualization guidelines and best practices for complex data types; Multiple data visualization tools (for example, Python, R libraries, GGplot, Matplotlib, Ploty, Tableau, PowerBI etc.); Advanced visualization techniques/ tools; Multiple story plots and structures (OABCDE); Communication & influencing technique; Emotional intelligence. To identify and recommend the most suitable visualization tools based on context. Generate appropriate graphical representations of data and model outcomes. Understand customer requirements to design appropriate data representation for complex data sets and drive User Experience designers and User Interface engineers to build front end applications. Define application design based on customer requirements. Build compelling stories based on context to integrate multiple pieces of information into cohesive insights. Present to and influence audiences using the appropriate data visualization frameworks and conveys clear messages through deep business and stakeholder understanding. Customize communication style based on stakeholders and leverages relationships to drive behavioral change. Guide and mentor junior associates on story types, structures, and techniques based on context. Analytical Modeling: Requires knowledge of feature relevance and selection; Exploratory data analysis methods and techniques; Advanced statistical methods and best-practice advanced modelling techniques (e.g., graphical models, Bayesian inference, basic level of NLP, Vision, neural networks, SVM, Random Forest etc.); Multivariate calculus; Statistical models behind standard ML models; Advanced excel techniques and Programming languages like R/Python; Basic classical optimization techniques (e.g., Newton-Rapson methods, Gradient descent); Numerical methods of optimization (e.g. Linear Programming, Integer Programming, Quadratic Programming, etc.) To select appropriate modeling techniques for complex problems with large scale, multiple structured and unstructured data sets. Select and develop variables and features iteratively based on model responses in collaboration with the business. Conducts exploratory data analysis activities (for example, basic statistical analysis, hypothesis testing, statistical inferences) on available data. Identify dimensions and designs of experiments and create test and learn frameworks. Interpret data to identify trends to go across future data sets. Create continuous, online model learning along with iterative model enhancements. Develop newer techniques (for example, advanced machine learning algorithms, auto ML) by leveraging the latest trends in machine learning, artificial intelligence to train algorithms to apply models to new data sets. Guide the team on feature engineering, experimentation, and advanced modeling techniques to be used for complex problems with unstructured and multiple data sets (for example, streaming data, raw text data). Model Assessment and Validation: Requires knowledge of model fit testing, tuning, and validation techniques (e.g., Chi square, ROC curve, root mean square error etc.); Impact of variables and features on model performance To identify and review model evaluation metrics based on analytical requirements. Apply suitable techniques for model testing and tuning, to assess accuracy, fit, validity, and robustness. Ensure testing information is documented and maintained by the team. Model Deployment and Scaling: Requires knowledge of impact of variables and features on model performance; understanding of servers, model formats to store models. To deploy models or model ensemble and ensure sustainability and maintenance overtime. Implement model monitoring and model life-cycle management practices. Assist in creation of innovative user interfaces and support the use of models through collaboration with key stakeholders. Drives the execution of multiple business plans and projects by identifying customer and operational needs; developing and communicating business plans and priorities; removing barriers and obstacles that impact performance; providing resources; identifying performance standards; measuring progress and adjusting performance accordingly; developing contingency plans; and demonstrating adaptability and supporting continuous learning. Provides supervision and development opportunities for associates by selecting and training; mentoring; assigning duties; building a team-based work environment; establishing performance expectations and conducting regular performance evaluations; providing recognition and rewards; coaching for success and improvement; and fosters a culture of belonging. Promotes and supports company policies, procedures, mission, values, and standards of ethics and integrity by training and providing direction to others in their use and application; ensuring compliance with them; and utilizing and supporting the Open Door Policy. Ensures business needs are being met by evaluating the ongoing effectiveness of current plans, programs, and initiatives; consulting with business partners, managers, co-workers, or other key stakeholders; soliciting, evaluating, and applying suggestions for improving efficiency and costeffectiveness; and participating in and supporting community outreach events. Leadership Expectations Respect for the Individual: Demonstrates and encourages respect for all; builds a high-performing, team; seeks, and embraces differences in people, cultures, ideas and experiences; creates a workplace and equitable experiences where associates feel seen, supported and connected through culture of belonging so associates thrive and perform; drives a positive associate and customer/member experience for all; identifies, attracts, and retains the best, team members. Respect for the Individual: Creates a discipline and focus around developing talent, through feedback, coaching, mentoring, and developmental opportunities; promotes an environment allowing everyone to bring their best selves to work; empowers associates and partners to act in the best interest of the customer/member and company; and regularly recognizes others contributions and accomplishments. Respect for the Individual: Builds strong and trusting relationships with team members and business partners; works collaboratively and cross-functionally to achieve objectives; and communicates and listens attentively, with energy and positivity to motivate, influence, and inspire commitment and action. Acts with Integrity: Maintains and promotes the highest standards of integrity, ethics and compliance; models the Walmart values and leads by example to foster our culture;supports Walmarts goal of becoming a regenerative company by making a positive impact for associates, customers, members, and the world around us. Acts with Integrity: Follows the law, our code of conduct and company policies, and sets expectations for others to do the same; promotes an environment where associates feel comfortable sharing concerns and reinforces our culture of non