Microsoft is a company where passionate innovators come to collaborate, envision what can be and take their careers further. This is a world of more possibilities, more innovation, more openness, and the sky's the limit thinking in a cloud-enabled world. 

 

Microsoft Azure Data’s mission is to build the data platform for the age of AI, powering a new class of data-first applications and driving a data culture. ​​Within Azure Data, the Microsoft Fabric platform team builds and maintains the operating system and provides customers a unified data stack to run an entire data estate. The platform provides a unified experience, unified governance, enables a unified business model and a unified architecture. ​ 

The messaging & real-time analytics team is hiring a Principal Data Scientist to tackle challenges in both open-source and proprietary technologies related to analytics, cloud, AI, and storage systems among others. We work on novel technologies including analytics on GPUs, container technologies, graph databases, infrastructure and models for LLMs and data-science, machine learning for systems, and many other areas.

 

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

Establishes collaborative relationships with relevant product and business groups inside or outside of Microsoft Fabric and provides expertise or technology to create business impact. Takes initiative and drives activities such as technology transfers attempts, filing patents, or consulting for product or business groups. May publish research to promote receiving new intellectual property for business impact. 

 

Brings new technology and approaches into production by applying long-term data science efforts to solve immediate product needs. Collaborates with and bridges the gap between DS and development teams. Conducts thorough review of data science techniques used and highlights areas that have been missed or need reexamining. Identifies new evaluation approaches and metrics and invents new methodologies to evaluate models.

Independently and collaboratively writes efficient, readable, extensible code/model that spans multiple features/solutions. Contributes to the code/model review process by providing feedback and suggestions for implementation and improvement. 

 

Serves as an expertise within the domain. Gains deep knowledge in a complex or highly ambiguous service, platform, or domain. Shares knowledge of changes in industry trends and advances in applied technologies with engineers and product teams to apply advanced concepts to identify product needs and drive action toward solutions. 

Reviews business and product requirements and incorporates state-of-the-art research or previously tested solutions occurring at Microsoft and the academic field to formulate plans that will meet business goals. Identifies problems and develops strategy to resolve team or feature level problems. Provides strategic direction for the kinds of data used to solve problems.  

Embody our culture and values 

Qualifications

Required/Minimum Qualifications 

  • Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ 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 7+ 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 10+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
    • OR equivalent experience.
  • 5+ years of experience with one or more of the following languages: Python, R, SQL, C++/C#.
  • 1+ year working on GenAI products and LLM technologies.
  • 5+ years of industry experience leading data science efforts using ML, LLM, RLHF, SFT, 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/Additional Qualifications 

 

  • Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 12+ years related experience (e.g., statistics, predictive analytics, research)
    • OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 8+ years related experience (e.g., statistics, predictive analytics, research) OR equivalent experience.
  • Ability to function well in “startup-like” fast-paced environments, and deliver data science solutions that are both practical and analytically sound.
  • Knowledge and intuition of consumer-facing products and applications that leverage AI or other algorithmic techniques.  
  • Comfortable operating in a complex, cross-functional organization where collaboration with other teams is essential to the success of your team.
  • Experience with data engineering, investing in data architectures, and building experimentation platforms.
  • 3+ years experience presenting at conferences or other events in the outside research/industry community as an invited speaker.
  • 7+ years experience conducting research as part of a research program (in academic or industry settings).
  • 5+ years experience developing and deploying live production systems, as part of a product team.
  • 7+ years experience developing and deploying products or systems at multiple points in the product cycle from ideation to shipping.

Data Science IC5 - The typical base pay range for this role across the U.S. is USD $137,600 - $267,000 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 $180,400 - $294,000 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 will accept applications and processes offers for these roles on an ongoing basis.

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.

#azdat 

#azuredata 

Salary

$137,600 - $294,000

Yearly based

Location

Redmond, Washington, United States

Job Overview
Job Posted:
2 months ago
Job Expires:
Job Type
Full Time

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