Data Scientist

Data Scientist Company Overview: Walmart Global Tech is dedicated to leveraging advanced technology and data science to enhance operations, empower associates, and improve the customer experience for millions worldwide. You will contribute to high-impact projects that streamline service operations, optimize processes in Finance, People, and Associate Digital Experience (ADE), and create actionable insights that drive measurable business results. Role and Responsibilities of Data Scientist: You will design, develop, and deploy AI and machine learning solutions to solve complex business problems. You will translate business challenges into analytical problems, collaborate with cross-functional teams, and deliver scalable, data-driven solutions that enhance operational efficiency and customer experience. • Develop, test, and deploy AI and ML solutions, including data preparation, feature engineering, model training, evaluation, and deployment • Ensure solutions are aligned with business goals, scalable, and high-quality • Translate business challenges into analytical or machine learning problems • Apply statistical and computational methods to generate actionable insights • Collaborate with engineering, product, and business teams to implement data-driven solutions • Enhance operational efficiency and customer experience through innovative analytics and ML solutions Required Skills and Experience of Data Scientist: • Bachelor's degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, or related field with 3 years of experience, OR • Master's degree in the above fields with 1 year of experience, OR • 5 years of experience in analytics or a related field • Solid foundation in machine learning, statistical analysis, and data science • Practical experience developing and deploying AI/ML solutions, including exposure to LLMs and emerging agentic AI systems • Proficiency in Python, SQL, and modern ML frameworks • Experience building and maintaining scalable data science and AI/ML pipelines • Collaborative mindset and commitment to continuous learning and knowledge sharing Preferred Qualifications: • Master's degree in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, or Econometrics • Experience with open-source frameworks such as scikit-learn, TensorFlow, or PyTorch • Successful completion of assessments in Python, Spark, Scala, or R • Knowledge of digital accessibility and WCAG 2.2 AA standards to support inclusive product experiences Compensation and Benefits of Data Scientist: • Competitive compensation with performance-based incentive awards • 401(k) match and stock purchase plan • Paid maternity and parental leave • Paid time off (PTO) • Multiple health plans including medical, vision, and dental coverage About Walmart Global Tech: Walmart Global Tech is a people-led, tech-empowered organization where one line of code can impact millions of customers. Our team includes software engineers, data scientists, cybersecurity experts, and service professionals driving innovation in retail. We foster a collaborative, inclusive culture with opportunities for skill development, growth, and impactful work. Our global hubs include Bentonville, Arkansas, the San Francisco Bay area, and New York/New Jersey, supporting a diverse team that works together to reimagine the future of retail. FAQ: Q: What does a data scientist do? A: They analyze large datasets, build predictive models, and provide insights to help guide business decisions. Q: What skills are needed to be a data scientist? A: Key skills include programming (Python, R), statistics, data visualization, machine learning, and problem-solving. Q: Do data scientists need prior experience? A: Yes, experience in data analysis, modeling, or related projects is usually required, along with a relevant degree. Q: Is a data scientist role challenging? A: It can be demanding due to complex data, evolving technologies, and the need to translate insights into actionable business strategies.