Academic

The primary purpose of this position is research in the fields of advanced complex data modeling, data mining, and knowledge discovery in databases.

Overall Qualifications and skills

• Experience and skills in algorithm/models/inference in analysis and data mining
• Demonstrated excellence in publications

The top applicant will have three (3) years of data mining experience on the job and a Master's degree in Computer Science, Statistics, or related discipline -- OR -- a Bachelor's degree with five (5) years related experience. We are looking for a self-starter, able to judge well among competing paths to explore, with strong programming skills and keen quantitative ability, and who is eager to work with highly-motivated colleagues and clients.

University of Michigan-Health Management Research Center is a privately-funded research center, established in the health and behavior outcome research field, directed by Dr. Dee W Edington, fast growing unit located on the central campus of UM-Ann Arbor, is looking for talented and experienced individuals with strong data mining experience to join the team. We are pushing the frontier of healthcare and wellness via predictive modeling. Advanced analytics is our strength and envision more multidisciplinary research in the areas of statistics, machine learning, mathematics, artificial intelligence, simulation, operational research, economics, and complex systems. The successful candidate must have a strong background in statistical data analysis and data mining algorithms (proven), be able to work productively in a team environment and effectively present ideas to people of varying technical backgrounds.

Requirements:

• Strong academic profile with an emphasis on quantitative and programming coursework (e.g., in Mathematics/Statistics, Computer Science, Economics, Financial Engineering) in the post graduate training.
• >= 3 years experience working with large unstructured data sets, in the areas of data analyses and mining for the real-life applications.
• Expert Excel, Access and PowerPoint skills; experience with database query tools (e.g., SQL); and a basic understanding of data warehouse architecture are required.
• Strong proficiency (implement and inference) with more than one statistical analysis tools (e.g., SAS, SPSS, STATA, Matlab, Splus, R) is required.
• Strong knowledge in data mining algorithms and working experience with more than one data mining software is required.

The ideal candidate will have:

• BS/MS/PhD in Statistics or Computer Science with outstanding credentials.
• Broad competencies in inter-related areas.
• Prior publications in leading conferences/journals a plus.
• Deep knowledge of either Matlab or R/Splus or BUGS or SAS.
• Experience with kernel methods and graph based algorithms a bonus.
• Exposure to econometrics and/or financial data a boon.
• Experience in exploratory data analysis and in data mining processes.
• Proven knowledge of data mining and machine learning methods and tools.

The person is required to:

• Develop and prototype models employing advanced statistical and/or data-mining techniques as appropriate (regression, GLMs, clustering, decision-trees, neural networks, etc.)
• Develop new application specific techniques as appropriate (e.g., pattern detection, prediction, optimization)
• Recommend and initiate model redevelopment, and enhancements beyond prototypes as required.
• Adapt techniques to complex models.
• Rapid prototyping of new algorithmic ideas and concepts.
• Interact and work with researchers and database systems programmers within the UM-HMRC as well as others.

Compensation: DOE

We seek results oriented researchers who want to solve real problems that make a direct and measurable impact. These individuals should enjoy formulating problems based on needs, selecting, modifying and/or building appropriate tools or methodologies, and providing true end-to-end solutions for diversified challenging data mining and healthcare data research projects.

Contact:
Contact: To be considered for this opportunity please forward your CV with cover letter to kdd-info_et_umich_dot_edu