Senior Data Science & Engineer

Overview

Microsoft Cloud Hardware Infrastructure Engineering (CHIE) is the team behind Microsoft's expanding Cloud Infrastructure and responsible for powering Microsoft's "Intelligent Cloud" mission. CHIE delivers the core infrastructure and foundational technologies for Microsoft's over 200 online businesses including Bing, MSN, Office 365, Xbox Live, Skype, OneDrive and the Microsoft Azure platform globally with our server and data center infrastructure, security and compliance, operations, globalization, and manageability solutions. Our focus is on smart growth, high efficiency, and delivering a trusted experience to customers and partners worldwide and we are looking for passionate, high energy engineers to help achieve that mission.

The Cloud Hardware Analytics & Tools (CHAT) Team within SCHIE develops advanced analytical and tooling solutions to support and improve the quality of Microsoft Azure. We collect , manage and analyze data across the full Azure stack, HW & SW components, Silicon development processes, and much more. CHAT Data Analytics & Engineering , a branch of CHAT, provides data support, machine learning and artificial intelligence solutions, and advanced visualizations to cloud engineering and management partners. We are looking for a Data Engineer and Data Science expert to support our custom data analytics and visualizations platform as well and building the enablement of implementing AI solutions and analytics across our division. This high-impact role combines data engineering with data science, and will have direct contributions to Azure-level projects, including working with highly visible platforms through data-driven approaches. This role closely collaborates with other Data Engineers, Software Engineers, other Data Scientists, Program Managers, and HW Engineering teams.

We further use that data to power AI solutions across the SCHIE org designed to improve efficiency, quality and innovation. If you're an experienced developer and share our passion please consider applying.

#azurehwjobs #SCHIE

Responsibilities

• Identify opportunities for custom and existing AI solutions that will provide business impact across our division.

• Design and develop data solutions to enable complex AI and analytical solutions

• Understand and stay connected to industry AI solutions

• Work in collaborative environment

Qualifications

Required/Minimum Qualifications

• Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) 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 3+ 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 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
      • OR equivalent experience.
• 2+ years customer-facing, project-delivery experience, professional services, and/or consulting experience.

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

• Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science,
  • • OR related field AND 3+ years 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 5+ 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 7+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
    • OR equivalent experience.

Data Science IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 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 $158,400 - $258,000 per year.

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


This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.

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 with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.