Experienced Full Stack Data Scientist – Omnichannel Delivery Chain Strategy and Optimization

About Walmart Global Tech Imagine working in an environment where one line of code can make life easier for millions of people. That's what we do at Walmart Global Tech. We're a team of software engineers, data scientists, cybersecurity experts, and service experts in the world's leading store who make an epic impact and are at the forefront of the next retail disruption. People are why we innovate, and that power our innovations. We are people-led and tech-empowered. We train our team in the skillsets of the future and develop specialists like you to help us grow. We have roles for those chasing their first opportunity as well as those seeking the opportunity to define their career. Here, you can kickstart an excellent career in tech, benefit from new skills and experiences for every industry, or leverage your expertise to innovate at scale, impact millions, and reimagine the future of retail. Job Overview We're seeking an experienced Full Stack Data Scientist to join our CENTROID Data Science team, which develops innovative solutions to make significant and visible impact decisions in Network transformation at Walmart. As a key member of our team, you will play a critical role in solving complex problems, including Ambient and Perishable inbound network layout, center mile network flow optimization, last mile transportation and returns layout, stock placement and targets, and transportation and monetization strategies to provide Walmart with a competitive edge in the medium to long term. Key Responsibilities - Develop and implement data-driven solutions to optimize Walmart's omnichannel delivery chain strategy - Collaborate with cross-functional teams to identify business opportunities and develop data-driven recommendations - Design and implement advanced statistical and machine learning models to solve complex business problems - Develop and maintain large-scale data pipelines and architectures to support data-driven decision-making - Work with stakeholders to communicate complex technical concepts and results to both technical and non-technical audiences - Stay up-to-date with the latest advancements in data science, machine learning, and related technologies - Collaborate with other data scientists and engineers to develop and maintain a robust and scalable data infrastructure - Develop and maintain high-quality, well-documented code and models - Participate in code reviews and provide feedback to colleagues - Collaborate with other teams to integrate data science solutions into production environments Essential Qualifications - Ph. D./M. S. in a quantitative field, including Operations Research, Mathematics, Computer Science, and Statistics, with up to ten years of relevant work experience - Ability to leverage your thesis in Operations Research or Statistics or an equivalent quantitative area related to math programming strategies, stochastic programming, or associated implemented disciples that used operations research modeling heavily - Experience with one or more of optimization toolkits/libraries, such as CPlex, Gurobi, XPressMP, or open-source solvers - Strong software development skills in languages, including Python, and familiarity with machine learning libraries, including Scikit, TensorFlow, PyTorch, and Keras - Ability to communicate complex technical concepts and results to both technical and non-technical audiences - Ability to collaborate with past useful leaders Preferred Qualifications - Established potential as a full-stack data scientist who develops, optimizes, and scales models for the production environment - Established potential with optimization modeling strategies (Linear Programming, Mixed Integer Programming, Non-Linear Programming) as well as advanced statistical modeling strategies (e.g., SVM, Random Forest, Bayesian inference, Graph models, NLP, Computer Vision, Neural Networks, etc.) - Experience with solving tough stock/operations planning problems. Experience solving stochastic discrete optimization problems using a lot of heuristics, integer programming models, and/or simulation-based approaches - Experience with Cloud technology, including GCP, Azure, as well as Spark, Hive, and TensorFlow, etc. - Strong track record of peer-reviewed publications Career Growth Opportunities and Learning Benefits - Opportunities to work on high-impact projects that can make a significant difference in the retail industry - Collaborative and dynamic work environment with a team of experienced data scientists and engineers - Opportunities for professional growth and development, including training and mentorship programs - Flexible work arrangements, including remote work options - Access to cutting-edge technologies and tools, including cloud-based platforms and machine learning frameworks - Opportunities to work on a wide range of projects, from data science to software engineering - Collaborative and dynamic work environment with a team of experienced data scientists and engineers Work Environment and Company Culture - Collaborative and dynamic work environment with a team of experienced data scientists and engineers - Flexible work arrangements, including remote work options - Opportunities for professional growth and development, including training and mentorship programs - Access to cutting-edge technologies and tools, including cloud-based platforms and machine learning frameworks - Opportunities to work on a wide range of projects, from data science to software engineering - Collaborative and dynamic work environment with a team of experienced data scientists and engineers Compensation, Perks, and Benefits - Competitive hourly rate of $65-$100 per hour - Incentive awards for performance - 401(k) match - Stock buy plan - Paid maternity and parental leave - Paid time off - Multiple health plans - Dental insurance - And many more benefits! How to Apply If you're a motivated and experienced data scientist looking for a new challenge, we encourage you to apply for this exciting opportunity. Please submit your resume and a cover letter explaining why you're the ideal candidate for this role. We can't wait to hear from you!