Director, Data Science

Walmart • Bentonville, AR

1d • $132,621 - $260,000 • Onsite

About The Position

The Director, Data Science will collaborate with stakeholders to support user interfaces and promote model usability at scale. This role involves writing code in languages such as SQL, Python, and Java, developing and testing features, creating POCs, deploying software, documenting code, and updating progress. The position requires applying relevant software testing techniques and best practices in visualization for complex data using tools like Tableau, PowerBI, Python, and R libraries. The Director will communicate insights through structured storytelling and influence decision-making through visual narratives. Key responsibilities include analyzing business problems, questioning assumptions, identifying root causes, and recommending technology-focused solutions. This includes defining success criteria, key metrics, and quantifying business impact. The role also involves translating business requirements into strategies aligned with organizational goals, evaluating business cases, articulating ROI, and challenging assumptions to deliver demonstrable value. Defining and identifying suitable data sources, performing data quality checks, and guiding junior associates on data selection are also crucial. Leveraging an understanding of business systems, distributed datastores (SQL, NoSQL), and success metrics to prioritize data needs is essential. The Director will select appropriate modeling techniques for large-scale, structured and unstructured data, conduct exploratory analysis, design experiments, and create test-and-learn frameworks. Developing models using advanced ML techniques and collaborating on feature development, as well as mentoring the team on experimentation and modeling methods, are key. Identifying model evaluation metrics, applying best practices for testing and tuning, and assessing model accuracy, fit, and robustness are required. Documenting testing processes to ensure validation quality and deploying models while ensuring sustainability through lifecycle management and monitoring practices are also part of the role. The role will supervise 2 Staff Data Scientists, 3 Data Scientists, and 4 Senior Data Scientists.

Requirements

• Managing a team of data scientists that implement AI/ML solutions in area of Fraud modeling
• Training and deploying supervised classification models using Python/Spark to detect fraud in real-time
• Training and deploying unsupervised network & cluster models using Python/Spark to detect fraud anomalies
• Mining large datasets to discover transaction patterns, examine retail data (orders, sales, returns) and isolate targeted information using traditional & advanced data science techniques
• Designing and developing KPI reports using SQL & Tableau to monitor real-time performance of models
• Implementing Machine Learning algorithms including Supervised (Regression/LASSO, SVM, Neural Networks, etc..) and Unsupervised (Association, Clustering, etc.)
• Conducting data and model drift analysis on production environment to identify inconsistencies & anomalies
• Utilizing statistical & data management tools & languages (Python, SQL, SAS) to provide insights & data solutions to business problems
• Working with a team from multiple disciplines, including engineering and product management to build new applications and improve business processes
• Azure / GCP for scalable deployment containerization (Docker, Kubernetes)
• Vector databases (Pinecone, Weaviate, FAISS, Milvus)
• Frameworks (LangChain, AutoGen, CrewAI, Haystack)

Responsibilities

• Collaborates with stakeholders to support user interfaces and promote model usability at scale.
• Writes code using appropriate languages (e.g., SQL, Python, Java) based on technical and business needs.
• Develops and tests features, creates POCs, deploys software, documents code, and updates progress.
• Applies relevant software testing techniques.
• Applies best practices in visualization for complex data using tools like Tableau, PowerBI, Python, and R libraries.
• Communicates insights through structured storytelling formats and influences decision-making through visual narratives.
• Analyzes business problems within their discipline, questions assumptions, and identifies root causes.
• Recommends technology-focused solutions, defines success criteria and key metrics, and quantifies business impact to create effective solutions.
• Translates business requirements into strategies and initiatives aligned with organizational goals.
• Evaluates business cases, articulates ROI, challenges assumptions, and delivers demonstrable value.
• Defines and identifies suitable data sources aligned with business requirements.
• Performs data quality checks and guides junior associates on data selection and quality.
• Leverages understanding of business systems, distributed datastores (SQL, NoSQL), and success metrics to prioritize data needs.
• Selects appropriate modeling techniques for large-scale, structured and unstructured data.
• Conducts exploratory analysis, designs experiments, and creates test-and-learn frameworks.
• Develops models using advanced ML techniques and collaborates on feature development.
• Mentors team on experimentation and modeling methods.
• Identifies model evaluation metrics and applies best practices for testing and tuning.
• Assesses model accuracy, fit, robustness, and documents testing processes to ensure validation quality.
• Deploys models and ensures sustainability through lifecycle management and monitoring practices.
• Supervises 2 Staff Data Scientists, 3 Data Scientists, and 4 Senior Data Scientists.

Benefits

• Walmart and its subsidiaries are committed to maintaining a drug-free workplace and has a no tolerance policy regarding the use of illegal drugs and alcohol on the job.

What This Job Offers

• Job Type: Full-time
• Career Level: Manager