2024 Summer Intern: Walmart Connect, Data Science,...

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.; To understand, articulate, and apply principles of the defined strategy to routine business problems. 

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; 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. 

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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, Python, SAS and/or others; To write code to develop the required solution and application features by using the recommended programming language and leveraging business, technical, and data requirements. Advanced excel techniques; Test the code using the recommended testing approach. 

Understanding Business Context:  

• Requires knowledge of Industry factors and relevant business metrics; Common business vernacular; Understand the specific business use cases and business practices across two or more domains such as product, marketing, sales, technology, and advertising; Drive delivery of project activity and tasks assigned under guidance, in solving business issues. 

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. 

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Data Visualization:  

• Requires knowledge of Visualization best practices; Multiple data visualization tools (for example, Python, R libraries, GGplot, Matplotlib, Ploty, Tableau, etc.); Advanced visualization techniques/ tools. 

Communication & influencing technique. 

• Able to communicate technical material to a range of audiences that provides insight into marketing performance. Generate appropriate insights of model outcomes. Support the understanding of customer requirements and design data sets appropriately to render meaningful insights; Present to and influence using the appropriate data insights and visualization frameworks and convey messages through basic business understanding. 

Build partnerships. 

• Build 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. 

Compliance minded. 

• Understand and comply 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 the data, insights, visualizations, and models. 

Minimum Qualifications:  

• Must be enrolled in an graduate, Masters degree program currently.  

• Expected graduation date between December 2024 and August 2025

• 0-1 years of full-time relevant experience  

• Proficiency with Microsoft 365 (Outlook, Word, Excel, PowerPoint) and SharePoint; Salesforce, Power BI, SQL experience is a plus 

• Python, SQL, SAS, R

• Statistics

• Machine Learning

• Modeling Optimization

Preferred Majors:

• Data Science
• Statistics
• Mathematics
• Operations Research
• Applied Economics.

Office Environment: 

Corporate, in-person internship

Job Location

We have opportunities available in the below locations for this role.

• Hoboken, NJ