Sorry, this listing is no longer accepting applications. Don’t worry, we have more awesome opportunities and internships for you.

Fraud Analytics

MLWIZ Team

Fraud Analytics

New York City, NY
Full Time
Paid
  • Responsibilities

    Develop and implement effective fraud authorization suppression strategies to mitigate false positives from fraud loss mitigation efforts for the branded credit card business while ensuring an appropriate balance between risk, operational cost, and customer experience. These may be simple strategies based on decision trees, to more complex analyses involving text mining, clustering , or other advanced techniques.

    Analysis of customer transaction data to develop and improve transactional or authentication fraud prevention strategies for diverse card present and card not present scenarios.

    Identify patterns to detect false positive trends by evaluating combinations or sequence of events from different data sources.

    Managing a group of fraud analysts.

    Support large scale projects including testing and deployment of new vendor scores or tools , as well as development of business cases for new technology

    Develop and review MIS reports and communicate the fraud results to the business

    Share best practices with partners

    Partner in root cause analysis and decision quality / defect reviews to identify strategy opportunities to improve performance

    Work within a business end to end agile framework where teams are cross - functional and empowered , activities are time boxed around specific outcomes , work is iterative and incremental and problems are solved in a modular and adaptive manner.

    "Lump Sum Payment Provided "

    Qualifications

    Bachelors degree in Statistics , Economics , Finance , Mathematics , Computer Science , or a related quantitative field , is required . An advance degree is highly desirable

    A minimum of 5 years of experience in applied analytics is required preferably in a risk management context

    People leadership experience

    Experience in the Banking / financial industry

    Experience in the agile methodology of iterative project management

    Experience in the fraud risk discipline in Credit cards or other consumer Banking products is desired

    Experience in implementing strategies into real time fraud prevention system is desired

    Strong analytical skills. Familiar with dataset environments

    Experience in statistical and data analysis in a at least one of the following statistical software packages or languages : SAS(required), SQL , R or Python.

    Experience with Unix desired

    Excellent organizational skills

    Excellent communication and presentation skills are required

    Ability to be flexible and work in a rapidly changing environment

    Must be extremely motivated with a desire to continuously learn and refine our processes