Machine Learning Scientist II - Insights, Data Engineering & Analytics Group

The Insights, Data Engineering & Analytics Group (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.

Scroll down the page to see all associated job requirements, and any responsibilities successful candidates can expect.

Machine Learning Scientist II - Insights, Data Engineering & Analytics Group

As a Machine Learning Scientist II in the IDEAs Group, you will be bringing relevant data into central systems to create a 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 machine learning approaches, forecasting, and causal inference models while thriving 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.

Responsibilities

• You will build advanced machine learning models (classifiers, reinforcement learning, recommendation engines, causal inference, and forecasting) 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.
• 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.
• Embody our culture and values.

Qualifications

Required Qualifications :

Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 2+ years of 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 1+ year(s) related experience (e.

g., statistics, predictive analytics, research).

• OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field.
• OR equivalent experience.
• 2+ years of experience building advanced machine learning models with impact spanning engineering, marketing, and finance, on areas such as : reinforcement learning, forecasting, Large Language Models (LLM), recommendation engines, causal inference models, etc.

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

• 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.
• 3+ years of experience with SQL, R, Python to implement statistical models, machine learning, and analysis (Recommenders, Prediction, Classification, Clustering, etc.

in a 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.

Applied Sciences IC3 - The typical base pay range for this role across the U.S. is USD $98,300 - $193,200 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $127,200 - $208,800 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here.

Microsoft will accept applications for the role until August 12, 2024.

Microsoft is an equal opportunity employer. Consistent with applicable law, 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.

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