Hiring for an all-encompassing global marketing and analytics company, which harnesses the power of rich data, groundbreaking technologies, engaging creative and transformative ideas to get the results our clients require.

They fuse data, insights, technology and creativity to connect customers with brands in the moments that matter, via the medium they- ll be most receptive to.

This team 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 Statistician is responsible for applying various statistical and data analysis techniques in support of a variety of analytic solutions.

Responsibilities:

- Provide quality, statistically valid analysis and related output

- Employ appropriate data analysis techniques and 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 under minimal supervision

- Apply basic analytical techniques to explore raw data, identify data issues, and QA/QC data and analysis output to ensure accuracy

- Manage multiple projects concurrently

- Monitor project progress relative to timeline and scope

- Create appropriate documentation for the analytical work

Essentials to the role & Background

- Bachelor's degree in a quantitative discipline (e.g., statistics, economics, mathematics, marketing analytics) or significant relevant coursework

- Minimum of 3 years of related experience

- Experience in SAS (strong) highly preferred

- Familiarity with 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

- Familiarity with SAS/SQL programming

- Working knowledge of MS Office; including PowerPoint, Word, Excel and Outlook

- Familiarity and basic knowledge of open source statistical programs like R, Python and KNime preferred

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