Senior Data Scientist

Microsoft Microsoft · Big Tech · Hyderabad, TS, IN · Data Science

Senior Data Scientist role within Microsoft's AI Engineering team in the Devices Operations (MDO) organization. The role focuses on developing and deploying AI experiences for supply chain, manufacturing, and device delivery operations. Responsibilities include partnering with stakeholders, framing problems, architecting and building production-grade AI systems (ML/DL, GenAI, optimization), and driving engineering excellence. Requires a strong background in data science and experience shipping production AI systems, ideally in operational environments.

What you'd actually do

  1. Partner with business stakeholders, Solution Managers, TPMs, and engineering teams to deeply understand business context, identify high-value AI opportunities, and design intelligent solutions that deliver measurable business outcomes.
  2. Frame complex operational problems into well-defined analytical and technical approaches, bridging business needs with production-ready AI capabilities.
  3. Architect and build production-grade AI systems (ML/DL, GenAI, optimization) using Azure AI, open-source, and custom models with full ownership from prototype to deployment.
  4. Drive engineering excellence: establish standards for code quality, MLOps, observability, testing, and secure deployment across the team.

Skills

Required

  • Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience
  • Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience
  • Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience
  • equivalent experience

Nice to have

  • Hands-on experience with Azure-native platforms: Fabric, Kusto, Databricks, Synapse, Azure ML Studio.
  • Background in supply chain, manufacturing, or hardware operations - understanding of demand planning, yield optimization, or logistics is a strong plus.
  • Experience building and maintaining MLOps infrastructure: CI/CD for models, automated retraining, drift detection, and rollout strategies.
  • Solid systems thinking — able to make pragmatic trade-offs between model performance, engineering cost, and operational simplicity.
  • Experience with optimization methods (linear/mixed-integer programming, simulation) applied to operational problems.

What the JD emphasized

  • production systems
  • production-grade AI systems
  • production solutions

Other signals

  • production systems
  • Generative AI
  • ML/Deep Learning
  • mathematical optimization
  • simulation
  • measurable impact