Data Scientist

Position: (USA) Staff, Data Scientist
Position Summary...

What you'll do...

Walmart Marketplace

Walmart Marketplace is a key part of e-commerce  is a gateway for Third-Party Sellers to manage their operations, such as onboarding, catalogs, order fulfillment, global opportunities, and return & refund management. We are responsible for providing the best in-class marketplace experience for our sellers and customers through the design, development, and operations of highly scalable systems. We interact with multiple teams within the company to develop scalable, robust technical solutions.

The data scientist role will be part of the data science team and will play a key role working along with others within the Marketplace engineering organization, product managers and business stakeholders to build Machine Learning products.

More about Marketplace:

What you'll do:
As a full stack Staff Data Scientist for Walmart, you will be responsible for building scalable end-to-end data science solutions for our data products.

* Own the MLOps lifecycle, from data monitoring to refactoring data science code to building robust model monitoring workflows for model lifecycle management

* Can develop and maintain scalable MLOps infrastructure, such as building Kafka pipeline for unified logging and monitoring across multiple projects.

* Apply SRE (Site Reliability Engineering) principles for ML workloads, optimizing cloud deployments, monitoring performance and troubleshooting application latency or operational issues.

* Lead code quality and engineering best practices by conducing code reviews, and mentoring junior MLEs.

* Can provide high-level architectural project guidance, break down complex tasks, and help resolve project challenges for the team.

* Build continuous, distributed and scalable training pipeline, inference pipeline and performance monitoring pipeline to be used across several Marketplace initiatives.

* Enhance data feedback/annotation workflows to improve efficiency of our labeling team

* Demonstrate strong thought-leadership and consult with product and business stakeholders to build, scale and deploy holistic machine learning solutions after successful prototyping.

* Collaborate cross-functionally with stakeholders to align AI solutions with Walmart's business objectives.

* Build and deploy end-to-end models, balancing accuracy, computational efficiency, and business impact.

What you'll bring:

* Very good knowledge of the foundations of machine learning and statistics

* Experience in machine learning, supervised and unsupervised and deep learning.

* Experience in analyzing the complex problems and translate it into data science algorithms

* Experience with big data analytics - identifying trends, patterns, and outliers in large volumes of data

* Strong Experience in Python with excellent knowledge of Data Structures

* Strong

Experience with big data platforms - Hadoop (Hive, Pig, Map Reduce, Scala, Spark)

* Hands on experience with Git

* Experience with SQL and relational databases, data warehouse

About Walmart Global Tech

Imagine working in an environment where one line of code can make life easier for hundreds of millions of people. That's what we do at Walmart Global Tech. We're a team of software engineers, data scientists, cybersecurity expert's and service professionals within the world's leading retailer who make an epic impact and are at the forefront of the next retail disruption.

People are why we innovate, and people power our innovations. We are people-led and tech-empowered. We train our team in the skillsets of the future and bring in experts like you to help us grow. We have roles for those chasing their first opportunity as well as those looking for the opportunity that will define their career. Here, you can kickstart a great career in tech, gain new skills and experience for virtually every industry, or leverage your expertise to innovate at scale, impact millions and reimagine the future of retail.

Walmart's culture is a competitive advantage, and it's fostered by being together. Working together in person allows us to collaborate, align quickly and innovate with greater speed. We use our campuses to create purposeful connection…