Senior, Data Scientist; GenAI​/LLM

What you'll do

We are seeking a highly motivated and skilled Senior Data Scientist to join Marketplace Applied AI team. You will play a critical part in driving data-driven decisions by developing advanced models, machine learning and computational algorithms. You will work closely with cross-functional teams to develop machine learning platform and services to optimize business processes and drive growth for Walmart Marketplace.

As a Walmart Senior Data Scientist, we are looking for a sharp, thoughtful, and collaborative problem solver, who enjoys uncovering key business drivers and challenges, and then building data science and analytics solutions to enable strategic decision making

Marketplace Applied AI team builds reusable technologies that aid in acquiring customers, onboarding and empowering merchants besides ensuring a seamless experience for both these stakeholders. We also optimize tariffs and assortment, adhering to the Walmart philosophy - Everyday Low Cost. In addition to ushering in affordability, we also create personalized experiences for customers the omnichannel way, across all channels - in-store, on the mobile app and websites.

Marketplace is the gateway to domestic and international Third-Party sellers; we enable them to manage their end-to-end onboarding, catalog management, order fulfilment, return & refund management. Our team is responsible for design, development, and operations of large-scale distributed systems by leveraging cutting-edge technologies in web/mobile, cloud, big data & AI/ML. We interact with multiple teams across the company to provide scalable robust technical solutions.

More about Marketplace:

• As a Senior Data Scientist for Global Marketplace team at Walmart, you’ll have the opportunity to
• Drive data-derived insights across the wide range of retail divisions by developing advanced statistical models, machine learning algorithms and computational algorithms based on business initiatives.
• Direct the gathering of data, assessing data validity and synthesizing data into large analytics datasets to support project goals.
• Utilize big data analytics and advanced data science techniques to identify trends, patterns, and discrepancies in data. Determine additional data needed to support insights.
• Build and train statistical models and machine learning algorithms for replication for future projects.
• Communicate recommendations to business partners and influencing future plans based on insights.
• Collaborate with cross-function teams to promote advanced modeling and algorithms into machine learning services and platforms.

• Experience with Data Source Identification:
  Requires knowledge of Functional business domain and scenarios;
  Categories of data and where it is held;
  Business data requirements;
  Database technologies and distributed data stores (e.g. SQL, No
  
  SQL);
• Experience with Data Quality:
  Existing business systems and processes, including the key drivers and measures of success. To Understand the appropriate data set required to develop simple models by developing initial drafts. Support the identification of the most suitable source for data Maintains awareness of data quality.
• Experience with Analytical Modeling:
  Requires knowledge of feature relevance and selection;
  Exploratory data analysis methods and techniques;
  Advanced statistical methods and best-practice advanced modelling techniques (e.g., graphical models, Bayesian inference, basic level of NLP, Vision, neural networks, SVM, Random Forest etc.) Basic classical optimization techniques (e.g., Newton-Rapson methods, Gradient descent);
  Numerical methods of optimization (e.g. Linear Programming, Integer Programming, Quadratic Programming, etc.)
• Advanced excel techniques and Programming languages like R/Python.
• Experience with coding language such as SQL and Python.
• Experience with language such as Java, C++ and other are preferred.
• Experience in Analyzing the Complex Problems and translate it into data science algorithms.

The above information has been designed to indicate the general nature and level of work performed in the role. It is not designed to contain or be…