(USA) Staff, Data Scientist

About the Role

Key Responsibilities

• Stay up-to-date with the latest machine learning and deep learning algorithms (Transformers, Multi-modal models) that power Personalization and Recommendations on Walmart.
• Utilize pre-trained embedding models such as T5, CLIP, Bert, and RoBERTa, and apply them to customer understanding and product recommendations.
• Stay proficient with big data technologies such as Hive, Spark, Google Cloud Platform (GCP), VertexAI, and Map-Reduce framework, and develop algorithms to handle massive web-generated data for data-driven inferences.
• Stay updated with data science and software engineering technologies used within the team, including Java, Hive, Map-Reduce, Python, Bash scripting, and machine learning packages like Scikit-Learn, Numpy, PyTorch, XGBoost, NLTK, and GenSim.
• Leverage data visualization tools such as Matplotlib, Seaborn, Plotly, and GGplot to showcase results.
• Apply best practices for model testing and tuning to assess accuracy and fit for data science models, including techniques like Chi square, F1, ROC curve, and root mean square error.
• Proactively acquire necessary data sources by communicating with stakeholders to ensure project success.
• Collaborate with personalization data engineering, modeling teams, and web service professionals to deliver key projects.
• Participate in designing components of the personalization backend system, from data collection to enabling data-driven decision making at scale.
• Research and innovate to develop new machine learning and AI techniques when existing methods do not meet business objectives.
• Work with cross-functional teams (engineering, MLOps, product, business) to deliver projects end-to-end.
• Utilize Large Language Models and productionalize them for industry-level deployment.
• Move fast and experiment with AI-assisted coding tools like Copilot to test hypotheses.

Requirements

• MS/PhD in Computer Science, Machine Learning, Operations Research, Applied Mathematics, Statistics, Engineering, or related field.
• 6+ years of relevant work experience in machine learning or data science.
• Deep background in NLP, Search Science, Recommendation Systems, Machine Learning, Deep Learning, Optimization, and Software development.
• Prior knowledge of Search or Recommendation Systems technology and Generative AI is highly preferred.
• Strong proficiency in Python, SQL, PySpark, and big data processing systems in cloud environments.
• Experience building ML models or delivering impactful customer-facing products as a technical lead and mentoring early-career data scientists.
• Experience with publications or patent filings is a plus.
• Expertise in Transformers, Multi-modal models, and their applications in personalization and recommendations.
• Proficiency with pre-trained embedding models such as T5, CLIP, Bert, and RoBERTa.
• Experience with data visualization tools like Matplotlib, Seaborn, Plotly, and GGplot.
• Strong skills in model assessment and validation techniques.

Nice to Have

• Data science, machine learning, and optimization models experience.
• PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, or Applied Mathematics.
• Successful completion of assessments in Python, Spark, Scala, or R.
• Experience with open source frameworks such as scikit-learn, TensorFlow, or PyTorch.
• Knowledge of creating inclusive digital experiences and implementing Web Content Accessibility Guidelines (WCAG) 2.2 AA standards.
• Experience with assistive technologies and digital accessibility best practices.

Qualifications

• Option 1: Bachelor's degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field with 5 years' experience in analytics.
• Option 2: Master's degree in relevant field with 3 years' experience in analytics.
• Option 3: 7 years' experience in analytics or related field.

Benefits & Perks

• Competitive pay with performance-based bonus awards.
• Health benefits including medical, vision, and dental coverage.
• Financial benefits such as 401(k), stock purchase, and company-paid life insurance.
• Paid time off including PTO, sick leave, parental leave, family care leave, bereavement, jury duty, and voting.
• Other benefits like short-term and long-term disability, company discounts, Military Leave Pay, adoption and surrogacy expense reimbursement.
• PTO and PPTO for vacation, sick leave, holidays, or other purposes, with amounts based on job classification and employment length.
• Live Better U education benefit program covering tuition, books, and fees for associates.