New 
Senior Data and Applied Scientist
 Microsoft | |
 United States, Washington, Redmond | |
 Jul 27, 2025 | |
|
OverviewThe 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 | |