Seeking highly motivated data scientist with strong analytical skills and prior experience in Card fraud strategies. Responsibilities will include performing advanced analyses utilizing multiple systems and databases to identify fraud patterns, mitigate risk, optimize decisioning strategies and minimize customer impact; partner with product, operations and technology teams to deliver real business impact; communicate with executive leadership and key stakeholder's risk observations and strategy performance; play significant roles in large-scale initiatives. Act as a resource for teammates with less experience. Perform sophisticated analytics (statistical and predictive analytics, machine learning modeling, etc.) to provide actionable insights that improve business outcomes and minimize risk and also provide consultation to business leaders and other stakeholders on how to leverage analytics insights and build strategies around analytics. ESSENTIAL DUTIES AND RESPONSIBILITIES Following is a summary of the essential functions for this job. Other duties may be performed, both major and minor, which are not mentioned below. Specific activities may change from time to time. 1. Independently perform sophisticated data analytics (ranging from classical econometrics to machine learning, neural networks, and natural language processing) in a variety of environments using structured and unstructured data. 2. Produce compelling data visualizations to communicate insights and influence outcomes among a wide array of stakeholders. 3. Take accountability and ownership of end-to-end data science solution design, technical delivery, and measurable business outcome. 4. Engage in stakeholder meetings to identify business objectives and scope solution requirements. 5. Independently write, document, and deploy custom code in a variety of environments (Python, SAS, R, etc.) to create predictive analytics applications. 6. Use, maintain, share and collaborate through Truist internal code repositories to foster continual learning and cross-pollination of skillsets. 7. Actively research and advocate adoption of emerging methods and technologies in the data science field, with the eye of continually advancing Truist's capabilities. 8. Exercise sound judgment and foster risk management culture throughout design, development, and deployment practices; partner with cross-functional teams to coordinate rules on data usage, data governance and analytics capabilities.
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Job Type
Full-time
Career Level
Mid Level
Industry
Credit Intermediation and Related Activities
Number of Employees
5,001-10,000 employees