Epsilon - Lead Statistician

Summary :

The Analytic Consulting Group partners with both internal and external clients, and data providers, leveraging predictive analytics and advanced statistical techniques to drive strategic thought and effective decision making. The Lead, Statistics is responsible for designing, planning, and managing statistical projects from start to finish.

Roles & Responsibilities:

- Ultimately responsible for the quality and statistical validity of all data and analysis results in the project

- Design, plan, and manage statistical projects from start to finish; serve as statistics lead on a project

- Master the desktop and UNIX/WINDOWS toolset (SAS, SAS ODS, R, Excel, PowerPoint, Word) to create content for evaluating statistical analyses such as tables, reports, graphs, etc.

- Supervise team members in data extraction and manipulation/aggregation

- Proficiently design, apply, and interpret various analytic techniques such as regression analysis (both linear and non-linear), cluster analysis, CHAID, factor analysis/principal component analysis, time series, survival models, experimental designs using SAS and other statistical software

- Provide proficient problem solving and data analysis based on modeling and statistical experience, as well as increasingly broad-based marketing and business experience

Minimum Qualifications :

- Bachelor's degree in a quantitative discipline (e.g., Statistics, Economics, Mathematics, Marketing Analytics) or significant relevant coursework

- Minimum of 5 years of related experience

- Mastery of various statistical methodologies such as regression analysis (both linear and non-linear), cluster analysis, CHAID, factor analysis/principal component analysis, time series, survival models, experimental designs using SAS and other statistical software

- Demonstrated proficiency in SAS/SQL programming

- Proficiency in at least one open source statistical programs like R, Python and KNime

- Strong analytic thought process and ability to interpret findings per quantitative discipline

- Database marketing experience/knowledge

- Working knowledge of Hadoop and other big data technologies