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Funding1M-5M USD
Employees190
SalaryShhhh...
FulltimeYes
TelecommuteNo
IndustrySoftware, Infrastructure
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Principal Data Scientist

at POISE in Collinsville CT 06022   —   Jun 30, 2014   |  
Overview
The Enterprise Data Warehouse at our client is seeking a Principal Data Scientist with the expert level statistical/predictive analysis and modeling skills to assist in the definition of strategic marketing plans relating to the profiling and segmentation of our e-commerce travel customer base. As a key member of the team, you will leverage your statistical expertise to define and analyze customer profiles utilizing demographics, geography, RFM, tenure, and spending patterns, as well as responses to marketing efforts to develop segmentation and predictive models, scoring and suitable KPIs. You will also utilize your strong communication skills to collaborate with other data warehouse operations team members to develop and apply appropriate models and segmentation to our customer base, providing decision makers with the empirical data required to identify underutilized customer segments and define the optimal marketing approach to those segments. Key areas include: Modeling and analytical skills; validating profile, segmentation and accuracy; advance multivariate statistical analysis; extract and cleanse large datasets; BI tools, etc.
Responsibilities
Demonstrated ability to apply modeling and analytical skills to real-world problems (ability to score/segment the entire customer base utilizing sophisticated statistical modeling such as discriminant analysis and/or predictive analytics)
Experience validating the customer profile, segmentation and scoring accuracy through the measurement of promotional responses across segments, and using results to build predictive models for future marketing promotions in order to market to the right segment in the right channel and with the right message
Expert-level fluency in applying advance multivariate statistical analysis (logistic & linear regression, decision tree, cluster analysis, and ANOVA) to categorize, classify, and detect data relationship in large datasets (not fitting memory)
Experience applying complex business logics to extract and cleanse large datasets from different data sources (xml, txt, xls, sql, etc)
Solid programming skills with knowledge of R, SAS, SQL, Python or other data-extraction and analysis tools and programming languages such as Java
Ability to understand complex business requirements and define KPIs to measure benefits and communicate complex quantitative analysis in a clear, precise, and actionable manner
Experience
Intermediate (4-6 years)
Skills
Advance multivariate statistical analysis (logistic & linear regression, decision tree, cluster analysis, and ANOVA)
Applying complex business logics to extract and cleanse large datasets from different data sources (xml, txt, xls, sql, etc)
Solid programming skills with knowledge of R, SAS, SQL, Python or other data-extraction and analysis tools and programming languages such as Java
Education
Ph.D. (or M.Sc. with equivalent level of experience) in Statistics, Operations Research, Computer Science, Mathematics, Machine Learning, Econometrics, Physics or related Quantitative disciplines (or equivalent level of experience)
Compensation
$75-90/hr
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