at Walmart
Full TimeAbout Team
The data science team at Walmart Global Tech focuses on using the latest in machine learning, statistics, software engineering and optimization to solve business problems. We mine data, distill insights, extract information, build analytical models, deploy Machine Learning algorithms, and use the latest algorithms and technology to empower business decision-making. In addition, we work with engineers to build reference architectures and machine learning pipelines in a big data ecosystem to productize our solutions. Advanced analytical algorithms driven by our team will help Walmart to optimize business operations, business practices and change the way our customers shop.
The data science community at Walmart Global Tech is active in most of the Hack events, utilizing the petabytes of data at our disposal, to build some of the coolest ideas. All the work we do at Walmart Labs will eventually benefit our operations & our associates, helping Customers Save Money to Live Better.
Your Opportunity
We are looking for a versatile principal data scientist– who has a strong expertise in machine learning engineering (and excellent software engineering skills) & also significant exposure to building ML solutions; including Gen AI solutions scratch up & leading data science engagement
The opportunities that will come with this role are –
As a seasoned SME in MLE, you will get to work on & take a lead in scaling & deployment for the most challenging of our data science solutions (including , but definitely not limited to Gen-AI solutions) across a broad spectrum of retail domains
Influence the best practices that we should follow as we scale & deploy our solutions across a diverse set of product.
Train and mentor our pool of data scientists in data sciences and MLE skills
Contribute to the Tech org via patents, publications & open source contributions.
What You Will Do
Design large-scale AI/ML products/systems impacting millions of customers •
Develop highly scalable, timely, highly-performant, instrumented, and accurate data pipelines
Identify, develop, and deliver improvements in data performance, data quality, and cost, which need to be monitored and analyzed
Drive and ensure that MLOps practices are being followed in solutions
Enable data governance practices and processes by being a passionate adopter and ambassador.
Drive data pipeline efficiency, data quality, efficient feature engineering, maintenance of different DBs (like Vector DBs, Graph DBs, feature stores, caching mechanism)
Lead and inspire a team of scientists and engineers solving AI/ML problems through R&D while pushing the state-of-the-art
Lead the team to develop production-level code for the implementation of AI/ML solutions using best practices to handle high-scale and low-latency requirements
Deploy batch and real-time ML solutions, model results consumption and integration pipelines.
Work with the customer-centric mindset to deliver high-quality business-driven analytic solutions.
Drive proactive optimisation of code and deployments, improving efficiency, cost and resource optimisation.
Design model architecture, optimal Tech stack and model choices, integration with larger engineering ecosystem, drive best-practices of model integrations working closely with Software Engineering leaders
Consult with business stakeholders regarding algorithm-based recommendations and be a thought-leader to deploy these & drive business actions.
Closely partners with the Senior Managers & Director of Data Science, Engineering and product counterparts to drive data science adoption in the domain
Collaborate with multiple stakeholders to drive innovation at scale
Build a strong external presence by publishing your team's work in top-tier AI/ML conferences and developing partnerships with academic institutions
Adhere to Walmart's policies, procedures, mission, values, standards of ethics and integrity
Adopt Walmart's quality standards, develop/recommend process standards and best practices across the retail industry.
Drive data pipeline efficiency, data quality, efficient feature engineering, maintenance of different DBs (like Vector DBs, Graph DBs, feature stores, caching mechanism).
Deploy batch and real-time ML solutions, model results consumption and integration pipelines.
Design model architecture, Optimal Tech stack and model choices, integration with larger engineering ecosystem, drive best-practices of model integrations working closely with Software Engineering leaders.
Drive proactive optimisation of code and deployments, improving efficiency, cost and resource optimisation.
What You Will Bring
Master's with > 13 years OR Ph.D. with > 10 years of relevant experience. Educational qualifications should be in Engineering / Quantitative sciences.
Strong experience working with state-of-the-art supervised and unsupervised machine learning algorithms on real-world problems.
Experience with web service standards and related patterns (REST, RPC).
Experienced in architecting solutions with Continuous Integration and Continuous Delivery in mind.
Strong experience in real time ML solution deployment
Strong Python coding and package development skills.
Experience with Big Data and analytics in general leveraging technologies like Hadoop, Spark, and MapReduce.
Ability to work in a big data ecosystem - expert in SQL/Hive/Spark.
Strong ability to architect ETL pipelines.
Strong ability to refactor data science code and has collaborated with data scientists and developing ML solutions.
Experience developing proper metrics instrumentation in software components, to help facilitate real-time and remote troubleshooting/performance monitoring.
Experience in GCP/Azure
Strong practitioner of MLOps principles
Champions and lead the way in cost optimization/Fin-Ops
Strong Experience in Python, PySpark & ability to optimize code in PySpark
Google Cloud platform, Vertex AI, Kubeflow, model deployment
Strong Experience with big data platforms – Hadoop (Hive, Map Reduce, HQL, Scala)
Experience with GPU/CUDA for computational efficiency
Experience in scaling Gen-AI solutions to work across multiple large data sets, architecture review, caching and Vector DB management, reducing latency and making the solution more robust and cost-efficient
Good effective communication (both written and verbal) skills and the ability to present complex ideas in a clear and concise way, to different audiences.
A technical leader and team player with a great work ethic
About Walmart Global Tech
From entry-level to executive positions, Walmart provides limitless opportunities for growth, and career development. Walmart started small, with a single discount store and the simple philosophy of selling more for less. Today, we are a growing technology-enabled company founded on the same values as our first store. We establish clear expectations, empower associates to manage their work, and hold ourselves and one another to a high standard. Walmart's scale enables us to have an. No other company has the reach of Walmart, with 2.3 million associates worldwide and over 230 million weekly customers. Walmart is reshaping retail by investing in an expanding workforce. While technology is at the heart of our digital transformation, people are the reason we succeed and the force behind our innovations. We train our team in the skillsets of the future and bring in experts like you to help us grow.
Flexible, Hybrid Work
We use a hybrid way of working with primary in office presence coupled with an optimal mix of virtual presence. We use our campuses to collaborate and be together in person, as business needs require and for development and networking opportunities. This approach helps us make quicker decisions, remove location barriers across our global team, be more flexible in our personal lives.
Benefits
Beyond our great compensation package, you can receive incentive awards for your performance. Other great perks include a host of best-in-class benefits maternity and parental leave, PTO, health benefits, and much more.
Equal Opportunity Employer
Walmart, Inc. is an Equal Opportunity Employer – By Choice. We believe we are best equipped to help our associates, customers, and the communities we serve live better when we really know them. That means understanding, respecting, and valuing diversity- unique styles, experiences, identities, ideas and opinions – while being inclusive of all people.
Outlined below are the required minimum qualifications for this position. If none are listed, there are no minimum qualifications.
Minimum Qualifications:Option 1: Bachelors degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 5 years' experience in an analytics related field. Option 2: Masters degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 3 years' experience in an analytics related field. Option 3: 7 years' experience in an analytics or related field.Outlined below are the optional preferred qualifications for this position. If none are listed, there are no preferred qualifications.
