Senior Data Scientist

Position: Senior Data Scientist 

Job Location: 811 Excellence Dr, 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. Understanding business context: Provide recommendations to business stakeholders to solve complex business issues. Develop business cases for projects with a projected return on investment or cost savings. Translate business requirements into projects, activities, and tasks and aligns to overall business strategy and develops domain specific artifact. Serve as an interpreter and conduit to connect business needs with tangible solutions and results. Identify and recommend relevant business insights pertaining to their area of work. Data source integration: support the understanding of the priority order of requirements and service level agreements. Help identify the most suitable source for data that is fit for purpose. Perform initial data quality checks on extracted data. 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:  Identify the model evaluation metrics. Apply best practice techniques for model testing and tuning to assess accuracy, fit, validity, and robustness for multistage models and model ensembles. Model Deployment and Scaling:  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. 

Minimum education and experience required: Master’s degree or the equivalent in Computer Science, Analytics, Mathematics or a related field plus 1 year of experience in analytics or related experience OR Bachelor’s degree or the equivalent in Computer Science, Analytics, Mathematics or a related field plus 3 years of experience in analytics or related experience. 

Skills required: Must have experience with: Using programming languages like SQL and Python to fetch, process and analyze data; Conducting Exploratory Data Analysis using packages like Pandas and NumPy; Performing missing data imputation as well as outlier detection and handling; Training machine learning models with packages like Scikit-learn and H2O; Evaluating model performance and optimizing it through feature selection and hyperparameter tuning; Developing, training, evaluating, and deploying machine learning or AI models in production environments; Explaining outputs from Machine Learning models using feature importance, SHAP and LIME; Time-series forecasting with ARIMA and Prophet; Leveraging version control systems such as Git; Generating data-driven insights to support decision-making processes; Using data visualization frameworks, such as Matplotlib and Plotly, to support visual identification of trends and patterns; Using cloud platforms such as AWS, GCP and Databricks; Designing and implementing scalable data pipelines, automating data workflows using Airflow, and using CI/CD tools such as Jenkins; Using tools like PySpark and Big Query to perform large scale data processing in a distributed environment; Containerization technologies like Docker and Kubernetes. Employer will accept any amount of experience with the required skills. 

  Rate of pay:  $94,557.00 - 180,000.00/year 

Wal-Mart is an Equal Opportunity Employer.