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Lead Data Scientist (Fraud Predictive Analysis)

Job Title
Lead Data Scientist (Fraud Predictive Analysis)
Job ID
1011821
Location
Ann Arbor,  MI 48104
Other Location
Description
Title:  Lead Data Scientist (Fraud Predictive Analysis)

Our History:
From our start in 2009, Conexess has established itself in 3 markets, employing nearly 150+ individuals nation-wide. Operating in over 15 states, our client base ranges from Fortune 500/1000 companies, to mid-small range companies. For the majority of the mid-small range companies, we are exclusively used due to our outstanding staffing track record

Who We Are:
Conexess is a full-service staffing firm offering contract, contract-to hire, and direct placements. We have a wide range of recruiting capabilities extending from help desk technicians to CIOs. We are also capable of offering project based work.

Summary
As our Lead Specialist - Fraud Predictive Analysis, your primary responsibility will be to develop and support our efforts to reduce credit card fraud with, “Card Not Present” and “Card Present” transactions.  You will interact with all levels of the organization and be involved in the day-to-day analytics of our fraud data.  The Fraud Data Analyst will also assist with retail point-of-sale data management. 

GENERAL RESPONSIBILITIES
  • Proactively identify trends, patterns, and profiles of fraudulent CNP (Card Not Present) ecommerce transactions. 
  • Lead analytics to achieve balance between fraud prevention and customer experience
  • Create rich, predictive data sets through collaboration with the data warehouse team
  • Create metrics, reports, analysis, visualization and the design of schemas and data flows to enable fraud reduction
  • Shape and guide fraud strategic reduction initiatives utilizing a disciplined analytic approach
  • Develop models that demonstrate incremental gains, while working under tight timeframes
  • Create and improve existing reports and dashboards using a variety of Business Intelligence tools.
  • Perform regular quality checks (QC) of large data sets and large data loads.
  • Assist with ad-hoc queries and data troubleshooting.
  • Integrate real-time fraud scoring of credit card data within our networks
  • Lead the identification of new opportunities for applications to do predictive analytics within Information Systems
  • Coach and develop other team members to enhance their predictive analytics skillset
  • Organize and present the final analysis into a clean and concise presentation to be delivered to key stakeholders within the business (including members of the executive team)

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