Senior Data Science Lead at Microsoft

Senior Data Science Lead Details

Nov. 1, 2018, 8:17 p.m.
Engineering
★★
Individual Contributor
Full-Time
Redmond, WA
The Data Science
Are you passionate about artificial intelligence and algorithm development? Do you enjoy learning new technologies and applying them to data problems? Can you work with a team of data scientists towards a common goal, and foster a culture of data and automation across an entire division? The Data Science team in Microsoft's Corporate, External, and Legal Affairs (CELA) group is looking for an experienced Data Scientist to join our team. This role will work closely with users dispersed globally across our department, as well as other data science groups across the company. The successful candidate will implement data infrastructure within CELA to enable machine learning, gain a deep knowledge of various data sources, understand the business processes that drive CELA, and initiate projects in collaboration with business partners. This individual will manage other data scientists and will report to the Director of Data Science in the Office of the President.

The core accountabilities of this role include: Build machine learning models using tools such as Python, R and Azure services. Provide AI expertise for various practice groups such as Intellectual Property, Immigration, Digital Crimes, Litigation, etc. Work with Project Managers to identify key analytics projects, and drive them from concept to production. Help individuals in your team grow professionally while contributing to CELA's digital growth.
The ideal candidate will be a strong performer with a rare blend of development and engineering skills, statistical expertise, and strong business acumen. The candidate should have the following skills and aptitudes: A self-starter who can work independently, pro-actively take action, drive toward clarity and think holistically. Deep knowledge of statistical theory, such as derivations for Bayesian formulas. Highly experienced with machine learning techniques such as neural networks, clustering, random forests, etc. Fluent in either R or Python, and at least one other language such as C#, C++,
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