Staff Data Scientist

What you'll do...

Position: Staff Data Scientist

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

Duties: Data Source Identification: Supports the understanding of the priority order of requirements and service level agreements. Helps identify the most suitable source for data that is fit for purpose. Performs initial data quality checks on extracted data. Data Strategy: Understands, articulates, and applies principles of the defined strategy to routine business problems that involve a single function. Model Assessment and Validation: Identifies the model evaluation metrics. Applies best practice techniques for model testing and tuning to assess accuracy, fit, validity, and robustness for multi-stage models and model ensembles. Data Visualization: Generates appropriate graphical representations of data and model outcomes. Understands customer requirements to design appropriate data representation for multiple data sets. Works with User Experience designers and User Interface engineers as required to build front end applications. Presents to and influences the team and business audience using the appropriate data visualization frameworks and conveys clear messages through business and stakeholder understanding. Customizes communication style based on stakeholder under guidance and leverages rational arguments. Guides and mentors junior associates on story types, structures, and techniques based on context. Understanding Business Context: Provides recommendations to business stakeholders to solve complex business issues. Develops business cases for projects with a projected return on investment or cost savings. Translates business requirements into projects, activities, and tasks and aligns to overall business strategy and develops domain specific artifact. Serves as an interpreter and conduit to connect business needs with tangible solutions and results. Identifies and recommends relevant business insights pertaining to their area of work. Tech. Problem Formulation: Translates/co-owns business problems within one's discipline to data related or mathematical solutions. Identifies appropriate methods/tools to be leveraged to provide a solution for the problem. Shares use cases and gives examples to demonstrate how the method would solve the business problem. Analytical Modelling: Selects appropriate modelling techniques for complex problems with large scale, multiple structured and unstructured data sets. Selects and develops variables and features iteratively based on model responses in collaboration with the business. Conducts exploratory data analysis activities (for example, basic statistical analysis, hypothesis testing, statistical inferences) on available data. Identifies dimensions and designs of experiments and create test and learn frameworks. Interprets data to identify trends to go across future data sets. Creates continuous, online model learning along with iterative model enhancements. Develops newer techniques (for example, advanced machine learning algorithms, auto ML) by leveraging the latest trends in machine learning, artificial intelligence to train algorithms to apply models to new data sets. Guides the team on feature engineering, experimentation, and advanced modelling techniques to be used for complex problems with unstructured and multiple data sets (for example, streaming data, raw text data). Model Deployment and Scaling: Deploys models to production. Continuously logs and tracks model behavior once it is deployed against the defined metrics. Identifies model parameters which may need modifications depending on scale of deployment. Code Development and Testing: Writes code to develop the required solution and application features by determining the appropriate programming language and leveraging business, technical, and data requirements. Creates test cases to review and validate the proposed solution design. Creates proofs of concept. Tests the code using the appropriate testing approach. Deploys software to production servers. Contributes code documentation, maintain playbooks, and provide timely progress updates.

Minimum education and experience required: Master’s degree or the equivalent in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field plus 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 plus 4 years of experience in analytics or related experience; OR 6 years of experience in analytics or related experience.

Skills required: Must have experience with: Product and AI/ML management; Implementing supervised and unsupervised Machine Learning techniques; Implementing Deep Learning and Reinforcement Learning methods; Implementing Operations Research and Mathematical Optimization approaches; Utilizing product skills, including discovery, backlog curation, persistent prioritization, road mapping, shepherding builds, collaboration with data scientists, and ownership of key business outcomes; Reframing of product activations and decision engines into ML/AI processes designed to achieve near and long term business impact objectives; Creating Agile prototypes to implement a unified consumer signal (i.e., optimization, causal DAGs, forecasting, and addressable market demand); Consolidating cross-functional planning and business choice framework; Performing discovery, assessment, and ML/AI reengineering of existing decision engines to enable connected and harmonized intelligence to achieve targeted business outcomes; Partnering with Operations and Product team on research and proposals for roadmap integrations of new and viable AI technologies including evaluation of third-party software; Partnering with Retail Analytics to develop insights and pilot measurement of concepts in support of Agile and Iterative improvement processes. Employer will accept any amount of experience with the required skills.

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Wal-Mart is an Equal Opportunity Employer.