• Collaborate with and influence internal and external business partners on risk issues that have a critical impact on the success of the company’s direct-to-consumer strategic objectives.
• Create and promote risk-based frameworks and strategies for optimizing the quality of risk model decisioning (e.g., minimize false positives and false negatives).
• Leverage data science tactics to identify and delineate behaviors into good user stories (i.e., virtuous behavior) from bad user stories (i.e., malicious behavior).
• Author and monitor the performance of macro and transactional fraud rules
• Develop and maintain a suite of advanced analytical methods, tools, and models, including machine learning models, to detect and prevent malicious activity on our network.
• Build advanced reports and dashboards with Power BI to visualize trends, highlight anomalies and drive near real time business decisions.
• Create a reporting environment that enables self-service of on demand and monthly reporting packages as well as ad hoc analytics related to key performance indicators
• Develop and maintain a continuous monitoring system to assess the operational effectiveness of critical risk functions.

• 5+ years of data analysis and modeling experience
• Big data environment with hands on coding experience within various traditional data and open source tools (SQL, SAS, Python, etc.)
• Advanced data visualization experience
• Excellent quantitative and analytic skills, including the ability to identify patterns, trends, insights, and perform risk/reward trade-off analytics
• Ability to build effective presentations to communicate analytical findings
• Effective cross-functional project, resource, and stakeholder, with ability to effectively drive collaboration across teams.
• Ability to make decisions independently with minimal guidance from management.

Education:

• Bachelor’s Degree required in statistics, mathematics, physics, economics, business or other analytical or quantitative discipline. Master's Degree preferred.