Researcher, Predictive Analytics

Company: Xerox Research Center
Location: Webster, NY
Web: www.xerox.com/innovation/business-technology-research/enus.html

The Xerox Research Center Webster is seeking a researcher in the area of Predictive Analytics to design, develop, and deploy state-of-the-art, data-driven predictive models to solve business problems using the latest and most appropriate technologies in machine learning, pattern recognition, statistical modeling, information retrieval or stochastic operations research (Markov decision processes and reasoning under uncertainty).

Applicants must have a strong background in data modeling and analysis with deep expertise in one or more relevant areas, including, but not limited to, dynamic regression, time series models, decision support, recommendation systems, information retrieval, stochastic process modeling, graph theory, and Bayesian forecasting. The applicant must demonstrate state-of-the-art knowledge and presence in the research and/or entrepreneurial community in this area.

The successful candidate will be a team player capable of developing scalable solutions that go into real products. This will include developing actionable business information by extracting, standardizing, and transforming text and unstructured data from various sources. The candidate is expected to work from theory to application and needs to be an independent thinker and problem-solver with the ability to work directly with diverse business groups, anticipate business needs, and develop tools and processes in order to meet these needs.

The candidate should have strong software skills with expertise in modeling languages such as R, SAS or Matlab and, preferably, programming languages such as Java, Python or C#. Experience with large scale datasets and Hadoop/Mahout is also highly desired.

Role/Responsibilities:
Main responsibilities include analyzing large set of data, building models (data clean-up & filtering, pattern identification & feature extraction, variable selection, experimentation with algorithms). Additional responsibilities include communicating with research and business teams in order to develop partnerships through cross-functional collaboration.

Requirements:

• A Ph.D. in a quantitative field (Statistics, Information Science, Machine Learning, Computer Science, Engineering) with a strong record of scholarship or entrepreneurship and work experience of 2-5 years.
• Proficiency in modeling environments such as R, SAS or Matlab.
• Preferred experience in programming languages such as Java, Python or C#.
• Preferred experience with large databases.
• Desire to turn theory into practice and solve market value problems.
• Ability to develop partnerships through cross-functional collaboration.
• Research or entrepreneurial experience with one or more predictive modeling domains, including, but not limited to, dynamic regression, time series models, decision support, recommendation systems, information retrieval, data mining, and Bayesian forecasting.
• Strong analytical as well as written, and verbal communication skills.

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