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Job description
What you’ll do at
Position Summary...
What you’ll do...
Job Summary:
As a Senior Data Scientist, you will develop, deploy, and optimize data-driven solutions to address Walmart’s operational and strategic needs.
You will work with large-scale datasets, implement machine learning models, and collaborate with cross‑functional teams to deliver robust, scalable, and efficient APIs and data systems.
Key Responsibilities:
Design, develop, and deploy machine learning models and algorithms to address key business challenges, including supply chain optimization, customer personalization, and operational efficiency.
Implement scalable data pipelines using PySpark and other big data tools to process and analyze large-scale datasets.
Build and maintain APIs for deploying machine learning models and integrating with business systems.
Collaborate with engineering teams to implement CI/CD pipelines, ensuring efficient and reliable deployment.
Optimize and maintain workflows for data processing and model training, focusing on performance, scalability, and reliability.
Apply best practices in software development, including code versioning, testing, and documentation.
Work closely with stakeholders to translate business needs into data‑driven solutions and actionable insights.
Key Qualifications:
Bachelor’s degree in computer science, Data Science, or a related field; advanced degrees are a plus.
4+ years of experience in data science, machine learning, or related fields.
Proficiency in Python and experience with libraries such as NumPy, Pandas, Scikit‑learn, TensorFlow, or PyTorch.
Hands‑on experience with big data tools and frameworks, including PySpark.
Proven track record of building and maintaining APIs for machine learning or data‑driven applications.
Knowledge of CI/CD pipelines and experience implementing automated workflows for model deployment.
Strong understanding of data pipelines, ETL processes, and scalable data handling techniques.
Excellent communication skills and a collaborative mindset.
Preferred Skills:
Experience with optimization, operations research, computer vision, and recommender systems.
Familiarity with distributed systems and parallel computing for performance optimization.
Background in applying statistical methods to real‑world business problems.
Benefits:
Competitive pay and performance‑based bonus awards.
Health benefits: medical, vision and dental coverage.
Financial benefits: 401(k), stock purchase plan, and company‑paid life insurance.
Paid time off: PTO (including sick leave), parental leave, family care leave, bereavement, jury duty, voting, short‑term and long‑term disability.
Additional benefits: company discounts, Military Leave Pay, adoption and surrogacy expense reimbursement.
Additional compensation includes annual or quarterly performance bonuses. Stock compensation may also be included for certain positions.
Minimum Qualifications:
Bachelor’s degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, or related field and 3 years’ experience in an analytics related field.
Master’s degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, or related field and 1 year’s experience in an analytics related field.
5 years’ experience in an analytics or related field.
Preferred Qualifications:
Data science, machine learning, optimization models.
Master’s degree in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics.
Successful completion of one or more assessments in Python, Spark, Scala, or R.
Experience with open source frameworks such as Scikit‑Learn, TensorFlow, Torch.
Background in creating inclusive digital experiences, knowledge of Web Content Accessibility Guidelines (WCAG) 2.2 AA standards, assistive technologies, and integrating digital accessibility seamlessly.
Primary Location: 805 Se Moberly Ln, Bentonville, AR 72712, United States of America
Annual Salary Range: $90,000.00 - $180,000.00
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Worksite address
bentonville, AR, 72712, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.