Senior Applied Scientist

Microsoft · Redmond

Company

Microsoft

Location

Redmond

Type

Full Time

Job Description

Do you have a passion for data and machine learning (ML)? Do you want to apply it to create security services that help millions of customers protect their applications from threat actors around the globe? Are you curious, analytical, and motivated by new challenges? If so, we would like to hear from you!

The Azure Anti-Fraud Team, which is part of the Microsoft Security Response Center (MSRC), is developing a cloud scale service that provides high precision detections for fraud and abuse activities across Microsoft Cloud. This solution is based on state-of-the-art machine learning and other techniques that rely on aggregating large-scale information. The team uses various detection strategies to identify evolving fraud patterns to combat fraud and abuse.

We are seeking a Senior Applied Scientist to help us grow and modernize our data science and detection strategies. As a Senior Applied Scientist on our team, you will partner with our engineers, other data scientists, and researchers to design, build, and deploy state-of-the-art machine learning to protect Microsoft Cloud. In your day-to-day work, you will build machine learning pipelines, vet experiments, incorporate quality monitors, and ship successful models to production.

You will have the opportunity to collaborate with partners across Microsoft who have decades of security research, and ML experience. Microsoft provides phenomenal community, tools, and technologists to grow your experience in this field.

Qualifications:

Required Qualifications:
  • 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.
  • 2+ years of programming experience in at least one of the following languages: Python, C++, C#, or similar language.
  • 2+ years of data querying experience in SQL or similar languages.
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:
  • Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research).
    • OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research).
    • OR equivalent experience.
  • 1+ year(s) experience developing and deploying live production systems, as part of a product team.
  • 1+ year(s) experience developing and deploying products or systems at multiple points in the product cycle from ideation to shipping.
  • Familiarity with ML tools & frameworks such as Jupyter notebook, ML.NET, CNTK/TensorFlow/PyTorch etc.
  • Familiarity with experiment design and applied machine learning for predicting outcomes in large-scale, complex datasets.
  • Experience in cloud services with prior exposure to Big Data technologies.
Applied Sciences IC3 - The typical base pay range for this role across the U.S. is USD $94,300 - $182,600 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 $120,900 - $198,600 per year.

Applied Sciences IC4 - The typical base pay range for this role across the U.S. is USD $112,000 - $218,400 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 $145,800 - $238,600 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: https://careers.microsoft.com/us/en/us-corporate-pay

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request via the Accommodation request form .

Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.

Responsibilities:

  • Provide technical leadership to our team by proposing and developing prediction models and implementing experiments.
  • Monitor and analyze data to uncover classification gaps.
  • Work with security threat analysts to identify performant features and models and make them accessible to our team.
  • Act as a resident consultant for machine learning, statistics, and experiment design.

Date Posted

08/09/2023

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