Python Programming, Scala Programming, Machine learning techniques, Marketing Strategy, Bayesian networks, Natural Language Processing (NLP), TensorFlow, Scikit-learn, R Programming, SPARK Programming, Neural Networks, Numerical Computing, Statistical modeling, Probabilistic Graphical Models, Multivariate analysis, Linear Models, Gradient Boosting trees, Torch library, Random forests, Integer Programming, Quadratic Programming, Decision Science, Newton Rapson methods
What you'll do...
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, and apply principles of the defined strategy to routine business problems that involve a single function.
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 the analytical modeling technique most suitable for the structured, complex data and develops custom analytical models. Conduct exploratory data analysis activities (for example, basic statistical analysis, hypothesis testing, statistical inferences) on available data. Define and finalize features based on model responses and introduces new or revised features to enhance the analysis and outcomes. Identify the dimensions of the experiment, finalize the design, test hypotheses, and conduct the experiment. Perform trend and cluster analysis on data to answer practical business problems and provide recommendations and key insights to the business. Mentor and guide junior associates on basic modeling and analytics techniques to solve complex problems.
Model Deployment and Scaling: Requires knowledge of impact of variables and features on model performance; understanding of servers, model formats to store models. To support efforts to ensure that analytical models and techniques used can be deployed into production. Support evaluation of the analytical model. Support the scalability and sustainability of analytical models.
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 using the recommended programming language and leveraging business, technical, and data requirements. Test the code using the recommended testing approach.
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 translate/ co-own business problems within one's discipline to data related or mathematical solutions. Identify appropriate methods/tools to be leveraged to provide a solution for the problem. Share use cases and gives examples to demonstrate how the method would solve the business problem.
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 Support the development of business cases and recommendations. Drive delivery of project activity and tasks assigned by others. Support process updates and changes. Support, under guidance, in solving business issues.
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 appropriate data set required to develop simple models by developing initial drafts. Support the identification of the most suitable source for data Maintains awareness of data quality.
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 support model fit testing and statistical inferences to evaluate performance. Assess the impact of variables and features on model performance.
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 generate appropriate graphical representations of data and model outcomes under guidance. Support the understanding of customer requirements and design data representations for simple data sets; Present to and influence the team using the appropriate data visualization frameworks and convey messages through basic business understanding.
Demonstrates up-to-date expertise and applies this to the development, execution, and improvement of action plans by providing expert advice and guidance to others in the application of information and best practices; supporting and aligning efforts to meet customer and business needs; and building commitment for perspectives and rationales.
Provides and supports the implementation of business solutions by building relationships and partnerships with key stakeholders; identifying business needs; determining and carrying out necessary processes and practices; monitoring progress and results; recognizing and capitalizing on improvement opportunities; and adapting to competing demands, organizational changes, and new responsibilities.
Models compliance with company policies and procedures and supports company mission, values, and standards of ethics and integrity by incorporating these into the development and implementation of business plans; using the Open Door Policy; and demonstrating and assisting others with how to apply these in executing business processes and practices.
Live our Values
Culture Champion
Servant Leadership
Embrace Change
Curiosity & Courage
Digital Transformation & Change
Deliver for the Customer
Customer Focus
Strategic Thinking
Focus on our Associates
Diversity, Equity & Inclusion
Collaboration & Influence
Talent Management
Contributes to an environment allowing everyone to bring their best selves to work, demonstrates engagement and commitment to the team, and recognizes others’ contributions and accomplishments.
Minimum Qualifications...
Outlined below are the required minimum qualifications for this position. If none are listed, there are no minimum qualifications.
Option 1: Bachelors degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 2 years' experience in an analytics or related field. Option 2: Masters degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field. Option 3: 4 years' experience in an analytics or related field.
Preferred Qualifications...
Outlined below are the optional preferred qualifications for this position. If none are listed, there are no preferred qualifications.
Data science, machine learning, optimization models, Master’s degree 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, Using open source frameworks (for example, scikit learn, tensorflow, torch)
Primary Location...
640 W California Avenue, Sunnyvale, CA 94086-4828, United States of America
About Walmart
At Walmart, we help people save money so they can live better. This mission serves as the foundation for every decision we make, from responsible sourcing to sustainability—and everything in between. As a Walmart associate, you will play an integral role in shaping the future of retail, tech, merchandising, finance and hundreds of other industries—all while affecting the lives of millions of customers all over the world. Here, your work makes an impact every day. What are you waiting for?
Walmart, Inc. 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 diversity- unique styles, experiences, identities, abilities, ideas and opinions- while being inclusive of all people.
Walmart Inc. is an American multinational retail corporation that operates a chain of hypermarkets, discount department stores, and grocery stores from the United States, headquartered in Bentonville, Arkansas. The company was founded by Sam Walton in 1962 and incorporated on October 31, 1969.
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