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Senior Data & Applied Scientist

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Microsoft Corporation

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Location:
United States , Redmond

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Category:
IT - Software Development

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Contract Type:
Not provided

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Salary:

119800.00 - 234700.00 USD / Year
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Job Description:

The AI Engineering team within MDO develops and deploys leading AI experiences that directly impact how Microsoft designs, plans, sources, manufactures, and delivers devices at global scale. Our multidisciplinary team - spanning data science, software engineering, and data engineering - delivers production solutions using Generative AI, ML/Deep Learning, mathematical optimization, and simulation, applied to real operational decisions with measurable impact. You will be a Senior Data & Applied Scientist and are a senior AI/ML practitioner who has shipped production systems in complex operational environments - ideally in supply chain, manufacturing, or sourcing. You combine deep technical expertise with business judgment to know which problems are worth solving and the engineering discipline to deliver solutions that last.

Job Responsibility:

  • 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
  • Frame complex operational problems into well-defined analytical and technical approaches, bridging business needs with production-ready AI capabilities
  • 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
  • Drive engineering excellence: establish standards for code quality, MLOps, observability, testing, and secure deployment across the team
  • Evaluate emerging AI tools/frameworks
  • advise on adoption decisions
  • Represent MDO as a technical SME in cross-Microsoft AI initiatives
  • Mentor and coach team members, raising the technical bar and fostering rigorous, inclusive innovation
  • Embody our Culture and Values

Requirements:

  • Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics predictive analytics, research) OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research) OR equivalent experience
  • 6+ years of professional experience delivering production AI/ML systems, including end-to-end model development, deployment, and monitoring
  • 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
  • Strong 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
  • Strong proficiency in Python and SQL
  • hands-on experience with cloud ML platforms (Azure ML, Databricks, or equivalent)
  • Experience with GenAI/LLM systems in production: RAG pipelines, prompt engineering, fine-tuning, or LLMOps (model versioning, evaluation, monitoring)
  • Demonstrated ability to work across engineering, product, and business teams to deliver outcomes not just models
  • Track record of communicating complex technical work to non-technical stakeholders in a clear, decision-ready manner

Additional Information:

Job Posted:
March 04, 2026

Employment Type:
Fulltime
Work Type:
Hybrid work
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