Senior Data Scientist

Walmart•Sunnyvale, CA

8d•$172,170 - $234,000•Onsite

About The Position

This role involves the design and deployment of scalable AI/ML systems within production-grade engineering frameworks at Walmart. The Senior Data Scientist will align technical solutions with strategic business objectives, refine advanced learning models through structured experimentation and parameter optimization, and design scalable data processing architectures supporting both streaming and batch operations. The position requires applying robust engineering principles to maintain modularity, version control, and reproducibility across analytical systems. Additionally, the role involves engineering data ingestion layers by orchestrating ETL pipelines across relational and NoSQL data stores, encapsulating model logic for seamless deployment, and leveraging statistical and temporal modeling techniques to extract insights and forecast trends. The Senior Data Scientist will translate complex business challenges into formalized data science solutions through end-to-end system design.

Requirements

Master’s degree or equivalent in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, or related field and 1 year of experience in an analytics related field; OR Bachelor’s degree or equivalent in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, or related field and 3 years of experience in an analytics related field.
Experience architecting and deploying scalable AI/ML systems within production grade engineering frameworks.
Experience leveraging SQL and NoSQL data platforms with optimized querying strategies.
Experience utilizing GCP services, Cloud Storage and BigQuery, for distributed dataset management and high throughput loading of large scale training and inference datasets across analytics workflows.
Experience designing and developing deep learning architectures using Python, TensorFlow, and PyTorch, and applying experimentation and hyperparameter tuning to ensure robustness.
Experience designing and managing distributed data pipelines with Pyspark and Hadoop and orchestrating workflows to support real-time and batch processing.
Experience applying software engineering principles including modular code design, object-oriented programming, and version control with Git to maintain high standards of code quality and reproducibility.
Experience containerizing models using Docker to simplify deployment and ensure compatibility across cloud platforms and enable seamless integration into production environments.
Experience applying statistical methodologies including probabilistic modeling and time series forecasting techniques to model temporal dependencies.
Experience executing comprehensive model evaluation using cross-validation, calibration checks, robustness and fairness assessments, and post-deployment drift monitoring.
Employer will accept any amount of experience with the required skills.

Responsibilities

Design and deployment of scalable AI/ML systems within production-grade engineering frameworks at Walmart, aligning technical solutions with strategic business objectives.
Refine advanced learning models through structured experimentation and parameter optimization to ensure performance and reliability.
Design scalable data processing architectures supporting both streaming and batch operations.
Apply robust engineering principles to maintain modularity, version control, and reproducibility across analytical systems.
Engineer data ingestion layers by orchestrating ETL pipelines across relational and NoSQL data stores, enabling scalable batch processing and fault tolerant analytical workflows.
Encapsulate model logic and dependencies to enable seamless deployment across varied environments.
Leverage statistical and temporal modeling techniques to extract insights, forecast trends, and support informed decision-making.
Translate complex business challenges into formalized data science solutions through end-to-end system design.