Job Description

Walmart's Advertising Technology group enables the connection between supplier brands and retail shoppers at unprecedented scale. We are a highly motivated group of engineers and data scientists, working in an agile group to solve sophisticated and high impact problems. We serve billions of ads requests every month with our high-performance ad servers. There are millions of customers shop on Walmart websites and in stores daily, and advertising helps advertisers bring the best products to our customers. If you want to influence millions of customers on their shopping journeys, we have a role for you.

The AdTech M&R data team is responsible for delivering reporting and measurement for Advertisers to analyze and optimize campaigns. We are a team of data developers and machine learning developers whose strengths are: (1) building scalable data pipelines (2) using machine learning techniques and data science (3) making sense of broadly defined problems through data analysis.

What you'll do...

• Build data systems that ingest, model, and analyze massive flow of data from online and offline user activities, processing hundreds of millions of sales and impressions data to obtain insights and analytics related to advertising campaign performance.
• Develop big data applications for precise audience targeting and cutting-edge measurement for campaign reporting, leveraging the wealth of data within the Walmart ecosystem.
• Set up ETL jobs in Jenkins or Airflow to move large volume of distributed data from various sources to secondary data centers for business continuity and disaster recovery.
• Troubleshoot business and production issues by gathering information (issue, impact, criticality, possible root cause), engage support teams to assist in resolution of issues, formulate an action plan, performing actions as designated in plan, interpret the results to determine further action, and complete online documentation.
• Develop complex software features to streamline and scale batch jobs to support advertising propensity models.
• Design, develop, and maintain software for the targeting and reporting data pipelines in Spark, Hadoop and Map-Reduce.
• Develop software using object-oriented languages such as Scala and Java. Implement advertising measurement systems that leverage machine learning and statistical techniques.
• Apply regression and classification machine learning methods in developing measurement products.
• Use Advanced big data scheduling techniques (Jenkins, Airflow) for reliable and recurrent data processing.
• Perform advanced data investigations using SQL and Spark or Hive.
• Design and develop systems and methods for ensuring quality for large data pipelines and guide the product through all stages of user acceptance process.

What you'll bring:

• Experience programming in an object-oriented language (Java or Scala).
• Experience in using Milvus and any kind of Vector database for building LLM application
• Experience using Hadoop and Map Reduce in batch jobs to process large scale data.
• 6+ years of software development experience, machine learning engineering or related field.
• Experience in creating and maintaining data processing workflows with tools including Airflow or Oozie.
• Experience using Spark, Hive, or SQL to perform advanced data investigation.
• Experience implementing statistical and machine learning methods for data classification and regression.
• Experience working in AdTech with demonstrated knowledge of the AdTech business.
• Experience developing techniques to ascertain correctness of data processing and transformation implementations using unit, integration, and end-to-end pipeline testing.
• Experience designing and developing software to perform ETL operations on large datasets.
• Experience building microservices.

Preferred experiences:

• PhD in data mining, database system, data management, machine learning, or statistic is a plus.
• Publications in top-tier academic conference and journal is a plus.
• Experiences with ad-tech targeting, measurement, identity mapping related domain is a plus.
• Patents in data or machine learn related domains is a plus.

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