Staff, Data Scientist (Recommendation)
About The Position
We are looking for a passionate, talented applied scientist experienced in the field of Recommender Systems, Information Retrieval, and/or Reinforcement Learning to invent and build scalable solutions for our marketplace goals. A successful candidate will have strong machine learning background and a desire to push the envelope in one or more of the above areas. The ideal candidate would also enjoy operating in dynamic environments, be self-motivated to take on challenging problems to deliver big customer impact, in fast moving iterative development cycles. The Personalization team at Walmart works on the mission to provide delightful customer experiences, increase customer engagement, and enable customer interactions to enhance business goals across different e-commerce touch points (e.g., W+, homepage, item page, deals and omni and marketplace). As an applied science team, we are responsible for pushing the boundaries and building cutting-edge scalable AI solutions (e.g. Large Language Model, Graph Neural Network, reinforcement learning models, multi-objective optimization models) that offer timely and personalized recommendations based on customers preferences to create relevant and meaningful experiences serving millions of customers across the globe. Our team creates reusable technologies to help with customer acquisition, onboarding, and empowering merchants, while ensuring a seamless experience for both of these stakeholders. We also optimize tariffs and assortment in accordance with Walmart's Everyday Low Cost philosophy. We not only create affordability, but we also deliver customized experiences for customers across all channels - in-store, mobile app, and websites.
Requirements
- PhD with 2+ years or MS with 5+ years of industry experience in Computer Science, Machine Learning, Mathematics, Statistics or Operational Research
- Must possess academic research or industry experience in implementing and scaling production grade modelling systems using machine learning algorithms, artificial intelligence, and deep learning models/techniques and advanced statistical models.
- A strong background in reinforcement learning, contextual bandits, short and long-term reward optimization paradigms.
- The candidate should be highly proficient in languages such as Java, Python, PySpark, and have experience with machine learning frameworks like Tensorflow and PyTorch, with the capability of using these technologies to design and develop high-performance applications.
- Strong knowledge in data analysis methods like dimensionality reduction, predictive modelling, clustering, text mining for effective feature engineering.
- The ability to innovate and solve complex problems, adapt to new technologies quickly, and find creative solutions for various business problems.
- Applicants must be authorized to work for any employer in the United States without current or future visa sponsorship.
- Bachelors degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 4 years' experience in an analytics related field.
- Masters degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 2 years' experience in an analytics related field.
- 6 years' experience in an analytics or related field
Nice To Haves
- Search recommendation experience strongly preferred.
- Data science, machine learning, optimization models
- PhD 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
- Using open source frameworks (for example, scikit learn, tensorflow, torch)
- We value candidates with a background in creating inclusive digital experiences, demonstrating knowledge in implementing Web Content Accessibility Guidelines (WCAG) 2.2 AA standards, assistive technologies, and integrating digital accessibility seamlessly.
- The ideal candidate would have knowledge of accessibility best practices and join us as we continue to create accessible products and services following Walmart’s accessibility standards and guidelines for supporting an inclusive culture.
Responsibilities
- Map the product and business requirements to a machine learning/AI problem.
- Research, design and implement scalable machine learning (ML) models for recommender systems, and/or other scalable computational models in an iterative product cycle.
- Perform hand-on analysis and modeling of large datasets to develop actionable insights.
- Create robust machine learning modelling systems with LLM, deep learning models as well as advanced statistical models which includes regression models, Bayesian models and online learning models to solve complex business problems.
- Work in a fast-moving cross functional environment with ability to collaborate with other teams over common product goals.
Benefits
- Incentive awards for performance
- 401(k) match
- Stock purchase plan
- Paid maternity and parental leave
- PTO
- Multiple health plans
- Competitive pay
- Performance-based bonus awards
- Medical coverage
- Vision coverage
- Dental coverage
- Financial benefits
- Stock
- Company-paid life insurance
- Paid time off benefits
- Parental leave
- Family care leave
- Bereavement
- Jury duty
- Voting
- Short-term disability
- Long-term disability
- Company discounts
- Military Leave Pay
- Adoption and surrogacy expense reimbursement
- PTO and/or PPTO that can be used for vacation, sick leave, holidays, or other purposes
- Walmart-paid education benefit program for full-time and part-time associates
- Tuition, books, and fees are completely paid for by Walmart
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
