Data and Applied Scientist at Microsoft

Data and Applied Scientist Details

Jan. 14, 2019, 7:53 p.m.
Engineering
Individual Contributor
Full-Time
Redmond, WA
and Platform team Microsoft Devices Supply
The Microsoft Devices Supply Chain (MSDSC) is responsible for the design, manufacturing, distribution, sales, and customer support of Microsoft's hardware products. The product portfolio includes Xbox One, Surface, Phones, Microsoft Band, HoloLens, Surface Hub and others spanning operations in hundreds of countries across online, retail, enterprise and operator channels. The pace of innovation and transformation within Devices Supply Chain is rapid as Microsoft continues to expand on product portfolio for Surface, Xbox, and accessories - building new business models, new fulfilment channels, new markets and exciting new products and services that help people and businesses throughout the world do more. This role will be a critical part of the Supply Chain Data Science and Platform team. The MSDSC Data Science and Platform team is looking for an experienced applied data scientist who is interested in being part of a result driven Data Science team that will drive decisions across the many

The successful candidate will have experience working with and analyzing data from a wide range of datasets and across a breadth of big data technology platforms. We are looking for people who see challenges as opportunities, people who can look at complex problems and are able to provide actionable insights and informed decisions using advanced analytics using machine learning and statistics. The ideal candidate can: Reframes specific questions to provide valuable context, and frames broad or ambiguous questions into discrete, manageable problems with well-defined, measurable objectives. Identifies
The ideal candidate has the following experience and background: Minimum of 3-5 years of relevant work experience in Advanced analytics using machine learning and statistics or in support of (building/engineering) data workflows specific to machine learning algorithms Proven ability to provide hands-on practical use of data and analytics Strong background in data science orientated workflows, and engineering patterns Statistics – Parametric, Non-parametric tests, Multivariate, PCA, Factor analysis Proven ability to translate business and product questions into analytics projects Experience working
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