Are you passionate about the idea of protecting over a billion people and making the world a durably safer place? The Microsoft Security Response Center (MSRC) is on the forefront of protecting the breadth of Microsoft’s customers from emerging threats to security and privacy.
The MSRC Data Science team is responsible for building data pipelines, data mining, Machine Learning (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 a Principal Data and Applied Scientist with experience to build reliable products and make business impact using data analysis, machine learning, experiments, data mining, data visualization, and more.
In this role as a Principal Data and Applied Scientist, we are looking for a technical leader deeply experienced to partner with a wide range of engineers, program managers, and researchers and bring in thought leadership to deliver solutions using Machine Learning and Statistics. This person 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 that would reveal useful insights, and eventually help engineering teams to operationalize data-driven 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.
Responsibilities
- Leverage subject matter expertise to 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.
- Establish, apply, and teach 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.
- Develop expertise in proper modeling, coding, and/or debugging techniques such as locating, isolating, and resolving errors and/or defects.
- 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, apply expertise 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.
Qualifications
Required Qualifications:
- Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years of 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 of 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 of data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
- OR equivalent experience.
- 5+ years customer-facing, project-delivery experience, professional services, and/or consulting experience.
Other Qualifications:
- 10+ years of professional experience in the software industry.
- 7+ years of professional experience in Machine Learning, Natural Language Processing, Deep Learning and related areas.
- 5+ years’ experience in building data pipelines using cloud computing like Python, Azure SQL database, Kusto (Azure Data Explorer), Azure ML, Azure Key Vault, Azure Storage or similar.
- 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 LLM (Large Language Models) using cloud-based tools like Azure OpenAI.
- Experience in developing on Azure ML, Azure SQL database, Azure Analysis Services, Azure Data Factory, Power BI or similar.
- Experience using technologies such as Big Data platforms.
Data Science IC5 - The typical base pay range for this role across the U.S. is USD $133,600 - $256,800 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 $173,200 - $282,200 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 is an equal opportunity employer. Consistent with applicable law, 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 and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.
