Senior Data Architect

The Microsoft AI for Good Research Lab leverages the power of data, our cloud technology, data science talent, and the Microsoft brand to catalyze and inspire others to partner in solving the world’s greatest challenges. Over the past five years, AI for Good Lab has become a data and AI driven solution creator, and trusted advisors working closely with leaders across Microsoft, academia, NGOs, UN agencies and all levels of government. Our mission is to use AI and technology to help organizations address the world’s greatest challenges.

As a Senior Data Architect, you get to work with some of the brightest minds in the field of Data Science, while knowing that you are generating solutions to some of the most demanding and defining challenges of our time. This role will report to the Director of Data Architecture, and work closely with teams across Microsoft to deliver world class solutions to some of the world’s most pressing problems.

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/Minimum Qualifications

• Bachelor's Degree in Computer Science, Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
  • OR Master's Degree in Computer Science, Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, or related field AND 3+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
  • OR Doctorate in Computer Science, Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
  • OR equivalent experience.

Additional or Preferred Qualifications

• Bachelor's Degree in Computer Science, Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, or related field AND 7+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results))
  • OR Master's Degree in Computer Science, Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
  • OR Doctorate in Computer Science, Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, or related field AND 3+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
• Experience with distributed computing frameworks (e.g., Spark), configuring, and running services in Kubernetes clusters. Experience contributing to Open Source Projects and with Threat Modeling.
• Experience with Azure ML services, and/or Azure Cognitive services, and/or TensorFlow and/or PyTorch.
• "Hands on" Experience creating Proof of Concepts, Minimum Viable Products (MVPs) for customers that lead to production deployments.

Data Science IC4 - The typical base pay range for this role across the U.S. is USD $117,200 - $229,200 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 $153,600 - $250,200 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 for the role until October 21, 2024.

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.

• Work closely with data analysts, data scientists, business, and project stakeholders to deliver data science solutions for a diverse set of problems. Help ensure security, privacy and compliance for all data assets and cloud resources.
• Design and implement Azure cloud architectures that support our data science and experimentation projects.
• Design and develop cloud-based data pipelines for data collection, analysis, and related functions.
• Provide thought leadership for technical architecture design, development, and deployment to support customer/partners data science scenarios. Identify technical blockers to accelerate architecture implementations and route non-technical issues for removal by the appropriate party.
• Share ideas, insight, and technical input with virtual team members using a working knowledge of Azure architectures and other relevant products. Actively look for relevant communities to learn from and contribute to.
• Participate in security peer reviews to identify and mitigate risks, including code reviews and threat modeling.
• Represent our capabilities and product offerings to internal and external leadership audiences, both technical and non-technical. Help advance the research agenda for AI For Good initiatives.
• Embodying our Culture and Values