Microsoft's Cloud & AI organization is looking to solve the problem of securing digital technology platforms, devices, and clouds in customer's heterogeneous environments, as well as ensuring the security of their own internal estate. The MSRC Data Science team specifically aims to build data pipelines, perform data mining, develop ML models, and generate insights on security-related data to provide unique insights into customer scenarios and lead a data-driven culture within security.
Requirements
- 2+ years related experience (e.g., statistics, predictive analytics, research) OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field OR equivalent experience.
- 2+ years’ experience in building data pipelines using cloud computing like, Kusto (Azure Data Explorer), Azure ML, Azure Key Vault, Azure Storage or similar.
- 1+ years of experience using GenAI and LLM.
- 3+ years of expertise with Python and experience with other scripting languages
- Experience with libraries such as Pandas, Keras, Pytorch, Scikit-learn etc. to build ML models.
- Experience in solving data science problems in Cybersecurity.
- Experience using technologies such as Big Data platforms
Responsibilities
- Data wrangling, data analysis and transforming large data sets to build scalable pipelines.
- Use Machine Leaning and Deep Learning techniques to build prediction models on structured and unstructured data.
- Improve the performance and run-time of ML models
- 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.
- Build data processing tools, libraries, frameworks and performing and getting insights from data analysis Learning and using tools like Azure ML, Azure Data Factory, Python and more public and Microsoft internal tools
- Ensure the solutions are stable, supportable, extensible, and trusted by our business partners.
Other
- Working with the business to understand a real-world scenario 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.
- Performs documentation of work in progress, experimentation results, plans, etc. Documents scientific work to ensure process is captured. Participates in the creation of informal documentation and may share findings to promote innovation within group.
- Collaborate with PMs to plan and prioritize ML deliverables as part of broader business initiatives, ensure delivery according to the planned schedule.
- Ability to meet Microsoft, customer and/or government security screening requirements are required for this role.
- Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.
