Staff Data Scientist

Position: Staff Data Scientist 

Job Location: 811 Excellence Dr, Bentonville, AR 72716 

Duties: Apply knowledge of analytics, big data analytics, automation techniques, business requirements, and relevant precedents to translate and co-own business problems within the discipline as data-related or mathematical solutions, identify appropriate methods and tools to address those problems, and share use cases and examples that demonstrate how selected methods solve the business need. Provide recommendations to business stakeholders to address complex business issues, develop business cases that reflect projected return on investment or cost savings, translate business requirements into projects, activities, and tasks aligned to overall business strategy, develop domain-specific artifacts, serve as a conduit between business needs and tangible solutions, and identify and recommend relevant insights related to the area of work. Support understanding of requirement prioritization and service-level agreements, help identify suitable data sources that meet fitness-for-purpose criteria, and perform initial data-quality checks on extracted data by applying knowledge of functional business domains, data categories, data locations, database technologies, distributed datastores, existing systems, and key business drivers. Select appropriate analytical modeling techniques for complex problems involving large, structured, and unstructured datasets; collaborate with the business to iteratively select and develop variables and features based on model responses; conduct exploratory data analysis including basic statistical analysis, hypothesis testing, and statistical inference; identify experiment dimensions and design test-and-learn frameworks; interpret data to identify trends across future datasets; create continuous online model-learning processes with iterative enhancements; develop newer techniques such as advanced machine-learning algorithms and AutoML; train algorithms to apply models to new datasets; and guide teams on feature engineering, experimentation, and advanced modeling for complex cases involving multiple or unstructured datasets. Identify model-evaluation metrics, apply best-practice model-testing and tuning techniques to assess accuracy, fit, validity, and robustness for multi-stage models and model ensembles, deploy models to production, continuously log and track deployed-model behavior against defined metrics, and identify model parameters requiring modification based on deployment scale. Write code using appropriate programming languages while leveraging business, technical, and data requirements, create test cases to validate proposed solution designs, develop proofs of concept, test code using suitable testing approaches, deploy software to production servers, contribute documentation and playbooks, and provide timely progress updates. Generate clear graphical representations of data and model outcomes, understand customer requirements to design effective representations for multiple datasets, collaborate with UX designers and UI engineers to build front-end applications, present and influence audiences using appropriate visualization frameworks, convey clear messages grounded in business and stakeholder understanding, tailor communication style appropriately, and guide and mentor junior associates on story types. 

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

Skills Required: Must have experience with: Utilizing Python and R programming to perform Supervised Learning, Unsupervised Learning, Natural Language Processing and Time Series Forecasting; Implementing Anomaly Detection, Data munging & Imputation, Statistical Hypothesis Testing to detect and identify trends and anomalies in data; Using SQL for data querying and analysis; Performing Unit Testing of code and GitHub Code version management for reliable development of ML solution; Designing and implementing Convolutional Neural Networks, Deep Learning (TensorFlow, Keras and PyTorch), Ensemble Methods, and Bayesian Inference; Leveraging Big Data Technologies for large scale datasets and solving optimization problems using Linear & Integer Programming; Applying Regularization and Hyperparameter Tuning for model improvements; Performing Cross-Validation for developing robust models with a focus on Model explainability; Applying Data Compression techniques to reduce dimensionality for model interpretability; Using PySpark to process large datasets in distributed computing environments; Working with Google BigQuery, Microsoft Azure Databricks to store, process and analyze large volumes of structured and unstructured data in cloud; Utilizing Tableau and Microsoft Power BI for effective presentation of insights from data; Leveraging SAP BW, SAP BOBJ, SAP Lumira, SAP Analytics Cloud, Analysis for Office, SAP Bex Explorer and Alteryx to support enterprise reporting and analytics workflows; Working with Teradata, SAP HANA, NoSQL, PostgreSQL to design, query relational and non-relational databases; Implementing CI/CD integration and MLOps (mlflow) practices for experiment tracking and model life cycle management; Operating within Agile (Scrum and Kanban) frameworks to deliver solutions. Employer will accept any amount of graduate coursework, graduate research experience or professional experience with the required skills. 

  Rate of pay:  $132,621.00 - 220,000.00/year 

Wal-Mart is an Equal Opportunity Employer.