Principal Data and Applied Scientist - Microsoft

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 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 hire people with a desire to build great products and make business impact using data analysis, machine learning, experiments, data mining, data visualization, and more.  We welcome applications from diverse multi-disciplinary backgrounds, with analytical skills, engineering abilities, communication skills, business interests, relentless curiosity, and a desire to improve the experiences of our customers. 

For this specific role, we are looking for a Principal Data and Applied deeply experienced using data to measure and improve Microsoft's security posture.  This high-impact position would initially require the technical lead 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. Not limited to the mentioned problem space, the ideal 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 that would reveal useful insights, and eventually help engineering teams to operationalize data-driven solutions.

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• 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 approach.
• 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 
• 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 early-in-career teammates and establish high 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 critical business decisions to improve reliability, scalability, and efficiency.

Required Qualifications

• 8+ years of professional experience in the software industry
• 6+ 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 Azure SQL database, Kusto, Azure ML, Azure Key Vault, Azure Storage or similar.
• Extract and solve core mathematical problems in complex questions, particularly strong skills in combinatorics, linear algebra, machine learning, cyber security, data profiling, and algebraic geometry
• Experience in Python, PySpark, SQL, and Kusto
• Theoretical background in statistics, machine learning, and algorithms
• Experience in solving data science problems in Cybersecurity.
• Experience with libraries such as Pandas, Keras, Pytorch, Scikit-learn etc. to build ML models.
• Attention to detail with self-discipline and a drive for results.
• Demonstrated ability to work in ambiguous situations and across organizational boundaries.
• Masters/PhD degree in Computer Science or related fields

Preferred Qualifications

• Experience in developing on Azure ML, Azure SQL database, Azure Analysis Services, Azure Data Factory, Power BI or similar.
• Experience in developing on DAX, ETL using Microsoft BI stack.
• Experience in Azure Synapse, Databricks, Azure Data Lake V2, Azure Purview, Virtual Machines
• Experience using technologies such as Big Data platforms

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. 

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.