Distinguished, Data Scientist

Position Summary...

What you'll do...

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 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 diverse 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. 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