Senior Machine Learning Scientist

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The Insights, Data Engineering & Analytics team (IDEAs), is a central data science team for M365 engineering and marketing. As one of the largest data science groups at Microsoft, our team plays a key role in providing data and analytics for M365 and owns the end to end ML and decision sciences charter. By joining our team, you will be at the heart of data, insights, machine learning, AI, and technology, lighting up actionable insights that drive key business decisions for the entire M365 organization.

As a Senior Machine Learning Scientist in IDEAs team, you will be bringing relevant data into a central systems to create the single version of truth and perform opportunity analysis and hypothesis generation for stages throughout the end-to-end customer lifecycle. This opportunity will allow you to gain expertise in designing, prototyping, implementing and testing descriptive, predictive analytics, forecasting, causal inference models and also thrive in a team environment that values cross team collaboration and building on the success of others.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

Required Qualifications:

• Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 8+ 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.
• 3+ years of experience with SQL, R, Python to implement statistical models, machine learning, and analysis (Recommenders, Prediction, Classification, Clustering, etc.) in big data environment.
• 2+ years of experience with written and verbal communication to educate and work with cross functional teams.
• 1+ year of experience in delivering on ambiguous projects with incomplete or imperfect data.

Other Requirements:

• Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings:
  • Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.

Preferred Qualifications:

• Bachelor's Degree in Statistics, Math, Computer Science, or related field AND 6+ years related experience (e.g., statistical, predictive, classification, clustering models; machine learning; analysis in big data environment)
  • OR Master's Degree in Statistics, Math, Computer Science, or related field AND 5+ years related experience (e.g., statistical, predictive, classification, clustering models; machine learning; analysis in big data environment)
  • OR Doctorate in Statistics, Math, Computer Science, or related field AND 3+ year(s) related experience (e.g., statistical, predictive, classification, clustering models; machine learning; analysis in big data environment)
  • OR equivalent experience.
• 3+ years of experience with SQL, R, Python to implement statistical models, machine learning, and analysis (Recommenders, Prediction, Classification, Clustering, etc.) in big data environment.
• Experience on large scale computing systems like COSMOS, Hadoop, MapReduce and/or similar systems.
• Experience with programming skills, e.g. Java, C#.
• Familiarity with deep learning toolkits, e.g. CNTK, TensorFlow.

• You will build advanced machine learning models (behavior segmentation, churn prediction, purchase propensity, recommendation engines, causal inference etc.) with impact spanning engineering, marketing, and finance.
• As you identify and explore opportunities for the application of machine learning, AI and predictive analysis, you will partner with teams across product, marketing, sales and engineering teams.
• You will work with engineers to architect and develop operational models that run at scale.
• You will communicate with technical and non-technical audiences, and contribute with your modeling expertise as a team player.
• You will tackle hard problems in innovative ways, drive self-directed initiatives, focusing on delivering the right results.