Data Scientist III

Posted 2 Days Ago
Be an Early Applicant
Bentonville, AR
Hybrid
Mid level
Big Data • Cloud • Logistics • Machine Learning • Retail
The Role
As a Data Scientist III, you'll analyze business problems and develop data-driven solutions using statistical modeling and machine learning techniques. You'll collaborate with stakeholders to understand business needs, identify data sources, and conduct exploratory data analysis. You'll also mentor junior associates and ensure the deployment and validation of analytical models while presenting insights for decision-making.
Summary Generated by Built In

What you'll do...

Position: Data Scientist III

Job Location: 702 SW 8th Street Bentonville, AR 72716

Duties: Tech. Problem Formulation: 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. 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. Understanding Business Context: 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. 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. Data Source Identification: 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. 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. Analytical Modeling: 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 Assessment and Validation: 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: 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. Data Visualization: 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. Data Strategy: understand, articulate, and apply principles of the defined strategy to routine business problems that involve a single function.

Minimum education and experience required: Master’s degree or the equivalent in Statistics, Analytics, Computer Science, or a related field OR Bachelor’s degree or the equivalent in Statistics, Analytics, Computer Science, or a related field plus 2 years of experience in analytics or related experience; OR 4 years of experience in analytics or related experience.

Skills required: Must have experience with: Coding in an object-oriented programming language: Python (pandas, numpy, SciPy), SQL (MySQL), R, Pyspark; Exploratory data analysis and dynamic data visualization using R (Ggplot), Python (matplotlib, seaborn), Tableau, Dataiku (automative dashboard), Microsoft Excel (Pivot Table) and show reports using the same; Developing statistical and machine learning models to make predictions using Python (Scikit-learn, TensorFlow, Numpy, Pandas), Dataiku(receipts); Applying appropriate analytical modeling/analysis, advanced statistical methods and machine learning modeling to resolve business problems: Neural Networks, Random Forest, Linear Regression, Logistic Regression, Classification, Clustering, sentiment analysis using python, XGBoost, SVM; Accessing and validating models using error metrics: confusion matrix, ROC curve, AUC, F1 score, precision, recall, accuracy, Mean Squared Error (MSE), Root Mean Squre Error (RSME), Mean Absolute Error (MAE), Symmetric Mean Absolute Percentage Error (SMAPE); Providing business insights and solutions based on business understanding and business problems by leveraging methods/tools; Database management and pipeline building using: SQL (CREATE TABLE, Primary Key, Secondary Key), Microsoft Access; Conducting experiments using probability, statistical analysis, hypothesis testing, statistical inferences in R; Python coding to write user defined functions, classes; Extracting, transforming and loading data from/to relational database (dataiku, Amazon Redshift, SQL); Presenting model output and assessing against business problems (Dataiku, Microsoft PowerPoint, Microsoft Excel, Python, Tableau); Data manipulation and data preparation using Python (numpy, pandas), SQL (window functions such as rank, row_number, lead, lag). Employer will accept any amount of graduate coursework, graduate research experience or experience with the required skills.

#LI-DNP #LI-DNI

Wal-Mart is an Equal Opportunity Employer.

Top Skills

Python
R
SQL
The Company
HQ: Bentonville, AR
578,950 Employees
Hybrid Workplace

What We Do

Walmart has a long history of transforming retail and using technology to deliver innovations that improve how the world shops and empower our 2.2 million associates. It began with Sam Walton and continues today with Global Tech associates working together to power Walmart and lead the next retail disruption. We’re a high-performing, primarily virtual workforce that is human-led and tech-empowered. Our world-class software engineers, data scientists and engineers, cybersecurity professionals, product managers and business service professionals work with top talent on cutting-edge technologies that create unique and innovative experiences for our associates, customers and members across Walmart, Sam’s Club and Walmart International. At Walmart Global Tech, one line of code or bold idea can make life easier for hundreds of millions of people – talk about epic impact at a global scale.

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