Fraud Strategy Manager / Full time hire

iShare Inc

Fraud Strategy Manager / Full time hire

Jersey City, NJ
Full Time
Paid
  • Responsibilities

    Hiring on behalf of a client for the role of

    Fraud Strategy Manager / Full time hire

    Location : NYC, Jersey City (3 - 4 days/week in office) (Open for Remote, if can join urgently)

    In this role, you will be involved in the First Party Fraud / Credit Abuse Strategy team for a leading US bank focusing on end-to-end delivery of analysis and seamless execution by collaborating with cross-functional teams. You will get an opportunity to derive insights from large complex datasets and impact business decisions through data-based findings.

    Responsibilities

    · Design & Implement data driven First Party Fraud/ synthetic frauds strategies, credit abuse.

    · Generate and automate regular reports and dashboards for fraud-related KPIs, offering actionable insights for Senior management.

    · Analyze transaction data and customer behavior to identify early warning signs of fraud and proactively address vulnerabilities.

    · Identification of potential check and deposits fraud - activity related to checks, such as forged checks, counterfeit checks

    · Independently address complex problems and share insights from data analysis that integrate with initial hypothesis and business objective

    · Comfortable working with large datasets, including managing large number of data sources, analyzing data quality, and pro-actively working with client's data/ IT teams to resolve issues

    · Reformulate highly technical information into concise business presentations

    · Create presentations and reports based on recommendations and findings

    Basic Qualifications

    · Bachelor's or master's degree in mathematics, statistics, economics, computer engineering or analytics related field

    · 4+ years of consulting, analytics delivery experience in Fraud, Disputes, operations and exposure to credit card & retail banking domains

    · Hands-on experience with SAS/SQL and Microsoft Office

    · Excellent communication, presentation and story building skills

    · Strong analytical skills with the demonstrated ability to research and make decisions based on the day-to-day complex customer problems

    Desired Qualifications

    · Ability to adapt to emerging analytic tools and solutions into standard operating procedures

    · Knowledge of basic machine learning algorithms like decision trees, regression models and clustering

    · Expertise in fraud application loss mitigation on cards portfolio