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Statistical/Econometric Modeler - 18-01253
Ref No.: 18-01253
Location: Mt. Laurel, New Jersey
Position Type:Contract
Start Date / End Date: 05/17/2018 to 12/31/2018
Primary purpose of this Role:

This role will be a critical component of Marketing Command Center project that will have hands on experience and subject matter expertise on Media & Digital Analytics with particular focus on building Media Mix Modeling.

Experience: 5-7 Years' experience preferably in Financial Industry or Retail/Client
Duties, Responsibilities and Accountabilities
  • Design, develop and implement various statistical and forecasting models to optimize different Direct to consumer, Media & Digital campaigns, risk, and response and customer value
  • Build predictive models using machine learning and statistical techniques and led applications of predictive modeling techniques for complex business problems such as multi-channel effectiveness, customer lifetime value modeling, social media sentiment analysis, digital marketing channels, media mix modeling and churn modeling
  • Provide leadership and creativity by using advanced quantitative methods to identify opportunities that bring value to the business and influence decision making.
  • Lead all analytic/modeling projects and provide solutions to the business problems facing across the cross functional department
  • Own  and manage model governance, and all regulatory affairs such as compliance approval process to make sure all the built models are in compliance with current banking rules and regulations
  • Synthesize data and analytical methods into actionable business strategy and communicate findings to business partners and executive management team 
Technical Skills: 
  • Requires an expert programming and modeling skills (e.g. expert in statistical/econometric  and machine learning software such as Base SAS, SAS EG, SAS EM, R, Python, Hadoop, Hive, Spark etc.) and database knowledge and query languages (e.g. Oracle, SQL etc.)
Experience & Education
  • 5-7 Years' experience preferably in Financial Industry or Retail/Client
  • Bachelor's degree  in Statistics, Operational Research, Applied Math, Engineering and or Computer Science (Master's Degree Preferred)