Senior Data and Applied Scientist

The Cloud & AI organization accelerates Microsoft’s mission and bold ambitions to ensure that our company and industry is securing digital technology platforms, devices, and clouds in our customers’ heterogeneous environments, as well as ensuring the security of our own internal estate. Our culture is centered on embracing a growth mindset, a theme of inspiring excellence, and encouraging teams and leaders to bring their best each day. In doing so, we create life-changing innovations that impact billions of lives around the world. Microsoft is one of the largest enterprise service companies in the world.

We are looking for a Senior Data and Applied Scientist to join our team! The MSRC Data Science team is responsible in building data pipelines, data mining, ML models and insights on security related data. We combine our data science work with business and engineering knowledge to provide unique insights into customer scenarios that are leading the data-driven culture within security.
We are looking for someone experienced in AI, Machine Learning and Statistics. This is a hands-on role, the candidate should be able to own one or more areas of opportunities and identify business or engineering problems, dig out sources of data, conduct the analysis and apply ML to solve and deliver solutions.

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.

In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positively impact our culture every day.

Responsibilities

• Business Understanding and Impact - Analyze problems and issues facing projects to uncover, manage, and/or mitigate factors that can influence final outcomes across product lines. Partner with business team to drive strategy and recommend improvements. Raise opportunities to look for new work opportunities and different contexts to use existing work. Establishes, applies, and teaches standards and best practices.
• Independently write efficient, readable, extensible code/model that spans multiple features/solutions. Contribute to the code/model review process by providing feedback and suggestions for implementation and improvement. 
• Lead and Scope out large quantitative projects and translate it into a machine learning problem and think of optimal ways of solving it. Outline alternative approaches and identify pros, cons, risks and provide recommended approaches.
• Identify data sources, integrate multiple sources or types of data,  within a data source to develop methods to compensate for limitations and extend the applicability of data.
• Transform formulated problems into implementation plans for experiments by applying (and creating when necessary) the appropriate methods, algorithms, and tools, and statistically validating the results against biases and errors
• Use broad knowledge of Machine Learning and Deep Learning innovative methods, algorithms, and tools from within Microsoft and from the scientific literature, and apply your own analysis of scalability and applicability to the formulated problem.
• Interpret data and communicate in a clear and lucid way to a wide variety of audiences.
• Validate, monitor, and drive continuous improvement to methods, and propose enhancements to data sources that improve usability and results.
• Mentor teammates and establish standards in both data science and engineering excellence.
• Keep up to speed with the current academic and industry advances in machine learning techniques, experiment with their application to improve our ML models.
• Work in collaboration with teammates to ensure reliable and trust-worthy data for business decisions to improve reliability, scalability, and efficiency.

• 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 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 of experience using Python, GenAI and LLM.

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: 

• 10+ years of professional experience in the software industry
  
• 5+ years of professional experience in Machine Learning, Natural Language Processing, Deep Learning and related areas.
• 3+ years’ experience in building data pipelines using cloud computing like, Kusto (Azure Data Explorer), Azure ML, Azure Key Vault, Azure Storage or similar.
• 2+ years of experience using GenAI and LLM.
• 5+ years of experience with Python and experience with other scripting languages
• Experience in solving data science problems in Cybersecurity.
• Experience with libraries such as Pandas, Keras, Pytorch, Scikit-learn etc. to build ML models.
• Exposure or knowledge of GenAI, LLM (Large Language Models) using cloud-based tool like Azure OpenAI
• Experience using technologies such as Big Data platforms

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: https://careers.microsoft.com/us/en/us-corporate-pay

Microsoft will accept applications for the role until July 31 2025.

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.

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