Staff, Data Scientist (mle)

Walmart Walmart · Retail · Bangalore, KA, India

Staff Machine Learning Engineer responsible for building scalable end-to-end data science solutions, owning the MLOps lifecycle, and deploying machine learning models in a large-scale enterprise environment. Focuses on scaling algorithms, monitoring, and productionizing solutions.

What you'd actually do

  1. Work closely with data engineers and data analysts to help build ML- and statistics-driven data quality and continuous data monitoring workflows
  2. Solve business problems by scaling advanced Machine Learning algorithms and complex statistical models on large volumes of data
  3. Own the MLOps lifecycle, from data monitoring to refactoring data science code to building robust model monitoring workflows for model lifecycle management
  4. Demonstrate strong thought-leadership and consult with product and business stakeholders to build, scale and deploy holistic machine learning solutions after successful prototyping.
  5. Follow industry best practices, stay up to date with and extend the state of the art in machine learning research and practice and drive innovation

Skills

Required

  • Machine Learning
  • Big Data Skills
  • Python
  • R
  • SQL/Hive
  • Spark
  • web service standards (REST, gRPC)
  • Continuous Integration and Continuous Delivery
  • distributed in-memory computing technologies
  • supervised and unsupervised machine learning algorithms
  • Python coding and package development
  • refactor data science code
  • metrics instrumentation

Nice to have

  • computer vision
  • forecasting
  • real-time analytics
  • conversational AI assistants

What the JD emphasized

  • building scalable end-to-end data science solutions
  • scaling advanced Machine Learning algorithms
  • MLOps lifecycle
  • deploy holistic machine learning solutions
  • taking solutions to production

Other signals

  • building scalable end-to-end data science solutions
  • scaling advanced Machine Learning algorithms
  • MLOps lifecycle
  • deploy holistic machine learning solutions
  • taking solutions to production