Staff Data Scientist

Walmart•Bentonville, AR

18h•$132,621 - $220,000•Onsite

About The Position

What you'll do... Position: Staff Data Scientist Job Location: 702 SW 8th Street, Bentonville, AR 72716 Duties: Data Source Identification: To 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. Data Strategy: To understand, articulate, and apply principles of the defined strategy to routine business problems that involve a single function. Model Assessment and Validation: Apply best practice techniques for model testing and tuning to assess accuracy, fit, validity, and robustness for multi-stage models and model ensembles. Data Visualization: To generate appropriate graphical representations of data and model outcomes. Understand customer requirements to design appropriate data representation for multiple data sets. Work with User Experience designers and User Interface engineers as required to build front end applications. Present to and influence the team and business audience using the appropriate data visualization frameworks and conveys clear messages through business and stakeholder understanding. Customize communication style based on stakeholder under guidance and leverages rational arguments. Understanding Business Context: To 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. Tech. Problem Formulation: To 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. Analytical Modeling: To select appropriate modeling techniques for complex problems with large scale, multiple structured and unstructured data sets. Select and develop variables and features iteratively based on model responses in collaboration with the business. Conducts exploratory data analysis activities on available data. Identify dimensions and designs of experiments and create test and learn frameworks. Interpret data to identify trends to go across future data sets. Create continuous, online model learning along with iterative model enhancements. Develop newer techniques by leveraging the latest trends in machine learning, artificial intelligence to train algorithms to apply models to new data sets. Guide the team on feature engineering, experimentation, and advanced modeling techniques to be used for complex problems with unstructured and multiple data sets. Model Deployment and Scaling: To deploy models to production. Continuously log and track model behavior once it is deployed against the defined metrics. Identify model parameters which may need modifications depending on scale of deployment. Code Development and Testing: To write code to develop the required solution and application features by determining the appropriate programming language and leveraging business, technical, and data requirements. Create test cases to review and validate the proposed solution design. Create proofs of concept. Test the code using the appropriate testing approach. Deploy software to production servers. Contribute code documentation, maintain playbooks, and provide timely progress updates.

Requirements

Must have experience with: Identifying business problems/process gaps and devise analytical, Data Science and ML solutions to address them
Writing production code in object-oriented languages like Java, C++, or Python
Designing, developing and deploying innovative Machine Learning, Deep Learning, Natural Language Processing (NLP), Gen AI, and Graph Neural Network (GNN) models using Python/GCP or other modeling tools
Designing and conducting A/B Testing and multivariate experiments (DOE), tracking results to provide actionable recommendations to business partners
Making sense of data using mathematical equations or statistical exploratory data analysis (EDA) methods using Python packages like NumPy, SciPy and Pandas
Working with large datasets and distributed datastores using SQL, finding insights, and telling stories using data
Developing clear, concise, and powerful data visualizations using BI tools like Power BI or Tableau
Constructing, managing, and monitoring scalable data pipelines using distributed computing frameworks like Spark and job schedulers like Airflow to aid in modeling and optimization products
MLOps practices including good design documentation, unit testing and source code control (git)
Engaging in code reviews, providing feedback to ensure the code is of excellent quality, maintainable and adheres to best practices
Master’s degree or the equivalent in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 2 years of experience in analytics or related experience; OR Bachelor’s degree or the equivalent in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 4 years of experience in analytics or related experience; OR 6 years of experience in analytics or related experience