Lead implementation of fraud risk strategies for consumer and commercial card businesses with decision engine systems in accordance with defined change control procedures and controls
Own and manage fraud rules, scores, and detection strategies, risk appetite execution, POS interdiction strategies and defect analysis
Lead gathering of business requirements, testing, and implementation of projects impacting fraud decision systems as well as system incidents
Leverage analytics to identify enhancement opportunities and more granular insights that can be acted upon, while ensuring adherence to Fraud Policy
Build effective relationships within and outside the Fraud organization to help ensure successful and timely execution of key portfolio priorities
Collaborate with cross-functional teams to provide strategy recommendations based on data and trend analysis and implement mitigation strategies
Continuously improve processes and strategies by exploring and evaluating new data sources, tools, and capabilities
Leverage customer data to build risk segmentation/ mitigation strategies and complete complex analyses to identify strategy and procedure gaps, manage implementation process across several systems to affect change
Lead key analytical projects within the card first party fraud analytics team and support the Card lines of business by utilizing advanced predictive analytical and statistical techniques
Translate data into consumer or customer behavioral insights to drive targeting and segmentation strategies, and communicate clearly and effectively to business partners and senior leaders all findings
Work closely with internal and external business partners in building, implementing, tracking, and improving fraud capture decision strategies
Refine framework for change control risk assessment including evaluation of control gaps within existing processes
Supports Governance process, evaluating historical performance and emerging changes in the environment
Prioritize and provide a clear line of sight to the most critical work to partners and team members
Mentor and coach junior team members

Requirements

Bachelor’s Degree required/Master's preferred in statistics, mathematics, physics, economics, or other (data) analytical or quantitative discipline
7+ years of experience required
6+ years of experience in analytics, modeling, or relevant area
Extensive experience working with: Big Data environment with hands on coding within various traditional (SAS, SQL, etc.) and/or open source (i.e. Python, Impala, Hive, etc.) tools
Traditional and advanced machine learning techniques and algorithms, such as Logistic Regression, Gradient Boosting, Random Forests, etc.
Data visualization tools, such as Tableau
Excellent quantitative and analytic skills; ability to derive patterns, trends and insights, and perform risk/reward trade-off analysis
Experience analyzing large datasets; applying mathematical, statistical and quantitative/data analysis techniques to perform complex analyses and data mining
Ability to build effective presentations to communicate analytical findings to a wide array of audiences
Effective cross-functional project, resource, and stakeholder engagement and management, with ability to effectively drive collaboration across teams
Ability to make decisions independently with minimal guidance from management
Experience with a prior focus in financial services analytics preferred

Benefits

medical, dental & vision coverage
401(k)
life, accident, and disability insurance
wellness programs
paid time off packages, including planned time off (vacation), unplanned time off (sick leave), and paid holidays

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

analyticsmodelingdata analysismachine learningLogistic RegressionGradient BoostingRandom Forestsdata miningquantitative analysisrisk/reward trade-off analysis

Soft Skills

communicationcollaborationproject managementstakeholder engagementmentoringcoachingdecision makingrelationship buildingprocess improvementanalytical thinking