REQUIRED/MINIMUM QUALIFICATIONS (RQS/MQS)

• Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND relevant data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
• OR Master’s Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND relevant years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
• OR Bachelor’s Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND relevant years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR equivalent experience.
• Customer-facing, project-delivery experience, professional services, and/or consulting experience.
• Proficient in Python with experience in Pandas, Scikit-learn, and the Python ML stack; strong coding skills for developing and maintaining machine learning models.
• Enjoy travel and are comfortable with travel up to 25%
• This role requires to have or be able to obtain SC clearance in the future.

PREFERRED QUALIFICATIONS

• Proficient in additional programming languages such as C#, Java, and C/C++.
• Skilled in building and maintaining models in various domains, including computer vision, forecasting, recommendation systems, and NLP.
• Experienced with agile development practices and Git version control.
• Familiar with deep learning frameworks like TensorFlow or PyTorch; experience with GenAI/LLMs is a plus.
• Experienced in the operational aspects of machine learning, including deployment, monitoring, and continuous integration of ML models.
• Relevant years of experience working with customers.
• Expertise in domains such as financial services, retail, marketing, healthcare, manufacturing, media, or telecommunications.
• Effective at communicating technical models in business and technical contexts.
• Comfortable with regional travel up to 25%.
• Familiarity with Spark, SQL, Graph stores, or NoSQL stores is helpful.
• MS or PhD in Computer Science, Electrical Engineering, Statistics, Operations Research, or an equivalent technical field.
  At Microsoft, we are seeking people who have a passion for the positive impact technology can have on communities and for making a difference in the world. Within ISE, you will find a wide range of backgrounds, perspectives, personal and cultural experiences which are vital to our success with our customers. It’s an informal and flexible work environment and you’ll be welcome to work in the way that best enables you to get your job done.
  We invest in your health, wellness, and financial future by offering a competitive package including a wide range of benefits built around your personal needs and those close to you.
  

  ISEngineering

Industry and Research Knowledge/Opportunity Identification

• Provides feedback, coaching, and support to engineering team and other teams based on business knowledge, technical expertise, and industry trends

Data Preparation and Understanding

• Manages data collection and preparation for projects. Handles data engineering also for production code.

Modeling and Statistical Analysis

• Applies machine learning solutions and algorithms to achieve objectives, prepare and evaluate data, and communicate findings and risks. Writes scripts in various languages and understands Microsoft AI and ML tools. Designs experiments and operationalizes models at scale. Coaches junior engineers on best practices.

Evaluation

• Understands relationship between selected models and business objectives. Ensures clear linkage between selected models and desired business objectives. Defines and designs feedback and evaluation methods. Coaches and mentors less experienced engineers as needed. Presents results and findings to senior customer stakeholders.
• Drive the development and adoption of Responsible AI practices, ensuring ethical, transparent, and compliant use of AI systems.

Industry and Research Knowledge/Opportunity Identification

• Provides feedback, coaching, and support to engineering team and other teams based on business knowledge, technical expertise, and industry trends.

  Coding and Debugging

• Demonstrates excellent coding and debugging skills across multiple features/solutions.

Customer & Partner Business Management

• Leads data-driven projects with business acumen and data science expertise.
• Drives business value by collaborating with stakeholders and improving solutions.
• Delivers customer-oriented solutions and builds trust with Microsoft products.

ML Engineering and MLOps

• Design and maintain scalable ML pipelines, feature stores, and training/inference systems to ensure reliable, high-performing models in production.
• Manage the full ML lifecycle—deployment, monitoring, retraining, CI/CD, and governance—for scalable, reliable, and compliant solutions.

Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.
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Industry leading healthcare
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Educational resources
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Discounts on products and services
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Savings and investments
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Maternity and paternity leave
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Generous time away
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Giving programs
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Opportunities to network and connect
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.