Senior, Data Scientist

Walmart · Retail · Bentonville, AR

Senior Data Scientist role focused on solving complex business problems in Ethics and Compliance using machine learning and optimization techniques. The role involves translating business requirements into technical solutions, building and processing large datasets, designing, implementing, and productionizing predictive and optimization models, and applying best practices for model testing and tuning. The position requires strong programming skills in Python and experience with distributed computing platforms and ML/DL frameworks.

What you'd actually do

  1. Be a strategic team member of the IROCC teams, sharing insights and providing recommendations through effective communication and storytelling with data.
  2. Translate business requirements to technical solutions in machine learning models, analysis, or software tools
  3. Share use cases and gives examples to demonstrate how the method would solve the business problem.
  4. Build complex data sets from multiple data sources, both internally and externally
  5. Process complicated and large-scale datasets using distributed computing platforms; extract insights from data.

Skills

Required

  • Python
  • PySpark
  • R
  • SQL
  • data mining
  • machine learning
  • statistical analysis
  • LLMs
  • NLP
  • CNN
  • RNN
  • transfer learning
  • attention mechanisms
  • large language models
  • transformers
  • generative models
  • embedding methods
  • classification
  • clustering
  • random forest
  • boosting
  • ensemble methods
  • data visualization
  • Map/Reduce
  • Hadoop
  • Hive
  • Spark
  • distributed computing
  • model testing
  • model tuning
  • Python
  • cloud
  • ML/DL
  • Docker
  • Kubernetes

Nice to have

  • R Shiny apps

What the JD emphasized

  • Productionize solutions (such as in the form of model servers or cron jobs)
  • Write solid production code, mainly in Python
  • Master and help evolve the team’s technical stack (centered on Python, cloud, ML/DL, Docker, Kubernetes)

Other signals

  • solve complex business problems using innovative data mining, machine learning and optimization techniques
  • Build complex data sets from multiple data sources
  • Process complicated and large-scale datasets using distributed computing platforms
  • Design, build, and implement predictive and optimization models
  • Productionize solutions (such as in the form of model servers or cron jobs)