Data Scientist

A global technology leader that develops software, cloud services, and business applications, known for Microsoft Dynamics 365 and Power Platform.
Data
Mid-Level Software Engineer
Hybrid
5,000+ Employees
4+ years of experience
AI · Enterprise SaaS

Description For Data Scientist

Microsoft's Business & Industry Copilots group is seeking a Machine Learning Scientist II / MLOps Engineer II to join their Customer Zero Engineering team. This role is crucial in building next-generation applications running on Dynamics 365, AI, and Copilot. The position focuses on developing and deploying machine learning models at scale, working with cutting-edge technologies in a cloud environment.

The ideal candidate will have 4+ years of experience in machine learning or MLOps, with strong expertise in cloud platforms, particularly Azure. You'll be responsible for the end-to-end lifecycle of machine learning models, from development to deployment and monitoring. The role requires proficiency in Python, ML frameworks, and containerization technologies.

Working in a hybrid environment with up to 50% work from home flexibility, you'll collaborate with cross-functional teams to build cohesive solutions. The position offers comprehensive benefits including healthcare, educational resources, and parental leave. This is an excellent opportunity to work with a leader in business applications and contribute to innovative solutions that impact organizations worldwide.

Microsoft's commitment to diversity and inclusion, combined with their mission to empower every person and organization, makes this an ideal opportunity for those looking to make a significant impact in the field of machine learning and AI operations.

Last updated a month ago

Responsibilities For Data Scientist

  • Design, build, and deploy machine learning models at scale
  • Develop and maintain MLOps/AIOPs pipelines
  • Implement CI/CD pipelines for ML models
  • Design and deploy monitoring and alerting systems
  • Optimize machine learning models and pipelines
  • Manage infrastructure for ML workloads
  • Partner with cross-functional teams
  • Provide technical guidance to junior engineers
  • Ensure ML lifecycle adheres to privacy and compliance requirements

Requirements For Data Scientist

Python
Kubernetes
  • 4+ years of experience in machine learning, MLOps/AIOPs, or software engineering roles
  • Experience with cloud platforms (Azure preferred) and infrastructure as code
  • Advanced knowledge of MLOps/AIOPs practices
  • Experience optimizing ML models for performance and scalability
  • Solid understanding of security and compliance frameworks
  • Proficiency in Python and ML frameworks (TensorFlow, PyTorch)
  • Experience with containerization (Docker, Kubernetes)
  • Strong knowledge of CI/CD tools and workflows
  • Understanding of model monitoring and governance practices

Benefits For Data Scientist

Medical Insurance
Education Budget
Parental Leave
  • Industry leading healthcare
  • Educational resources
  • Discounts on products and services
  • Savings and investments
  • Maternity and paternity leave
  • Generous time away
  • Giving programs
  • Opportunities to network and connect

Interested in this job?

Jobs Related To Microsoft Data Scientist

Technical Support - Fabric Data Engineering

Technical Support Engineer role at Microsoft focusing on Azure Databricks and Analytics Services, offering remote work and comprehensive benefits.

Data Engineer

Microsoft Data Engineer position focusing on big data, analytics, and fraud prevention systems using Azure technologies and cloud architecture.

Software Engineer

Software Engineer position at Microsoft Security focusing on data platform engineering and security services development.

Experimentation Program Manager

Microsoft seeks Experimentation Program Manager to lead A/B testing and user research initiatives for global eCommerce platforms, offering hybrid work and competitive benefits.

Data Engineer

Data Engineer role at Microsoft working on enterprise tax reporting systems using Azure technologies and big data solutions.