Senior Data Scientist

Position: Senior Data Scientist 

Job Location: 811 Excellence Dr., Bentonville, AR 72716 

Duties: Apply knowledge of feature relevance and selection, exploratory data analysis techniques, advanced statistical methods, and modeling approaches such as graphical models, Bayesian inference, basic natural language processing, computer vision, neural networks, support vector machines, and random forests. Utilize multivariate calculus, statistical foundations of machine learning models, advanced Excel techniques, and programming languages such as R and Python, along with classical and numerical optimization methods including Newton-Raphson, gradient descent, linear programming, integer programming, and quadratic programming. Select appropriate analytical modeling techniques for structured and complex datasets and develop customized analytical models. Conduct exploratory data analysis, including statistical analysis, hypothesis testing, and statistical inference, on available data. Define and refine features based on model performance, introducing new or revised features to improve analytical outcomes. Design experiments by identifying key dimensions, finalizing experimental design, testing hypotheses, and executing analyses. Perform trend and cluster analyses to address business problems and deliver actionable insights and recommendations. Apply knowledge of model fit testing, tuning, and validation techniques, including chi-square tests, ROC curves, root mean square error, and other relevant metrics. Identify appropriate evaluation metrics based on model objectives and business requirements. Assess the impact of variables and features on model performance and apply best-practice testing and tuning techniques to evaluate accuracy, fit, validity, and robustness across multi-stage models and model ensembles. Leverage understanding of model performance drivers, server environments, and model storage formats to support production deployment. Contribute to efforts ensuring analytical models and techniques are production-ready and operationally sustainable. Support model evaluation processes and enable scalability and long-term maintenance of analytical solutions. Utilize programming languages such as SQL, Java, C++, and Python, along with knowledge of business and domain requirements, to develop required solutions and application features. Apply appropriate testing methodologies, including static testing, dynamic testing, software composition analysis, and manual penetration testing, to ensure code quality, functionality, and security. 

Minimum education and experience required: Master’s degree or the equivalent in Computer Science, Statistics, Engineering (any), or related field plus 1 year of experience in analytics or a related field; OR Bachelor's degree or the equivalent in Computer Science, Statistics, Engineering (any), or related field plus 3 years of experience in analytics or a related field. 

Skills required: Must have experience with: Developing ML, Statistical and Transformer Based models for Tariff Calculation; Using NLP for text-based ML model designing and implementation; Coding in OOP Language – Python; Batch processing/ engineering across large scale data, scheduled processing using Airflow; Statistical analysis, A/B testing, Hypothesis testing and experimentation; Unsupervised Learning and Network Analysis; Designing and implementing data models and establishing unified data store; Building interactive dashboards in Tableau and perform data analysis in Excel, including pivot tables and charts for business stakeholders; Deploying ML models to the cloud for real time inference and batch processing, enabling scalable and efficient analytics; Developing Model monitoring framework for data drift and model drift analysis; Creating anomaly detection models and deploying in production; and Performing feature engineering, parameter tuning for model development. Employer will accept any amount of experience with the required skills. 

 Rate of pay: $90,000.00 - 180,000.00/year 

Wal-Mart is an Equal Opportunity Employer.