- Supports fraud strategy function develops 3 or more fraud rules per month while conducting analyses to identify underperforming fraud strategies that need to be retired
- In supporting rule analysis Teammate should be able to Independently perform sophisticated data analytics that fit to the fraud problem being observed ranging from classical econometrics to machine learning neural networks and natural language processing in a variety of environments using structured and unstructured data
- Produce compelling data visualizations to communicate insights and influence outcomes among a wide array of stakeholders
- Take accountability and ownership of end to end data science solution design technical delivery and measurable business outcomes
- Engage in stakeholder meetings to identify business objectives and scope solution requirements
- With minimal guidance write document and deploy custom code in a variety of environments Python SAS R etc
- to create predictive analytics applications
- Use maintain share and collaborate through Truist internal code repositories to foster continual learning and cross pollination of skillsets
- Actively research and advocate adoption of emerging methods and technologies in the data science field with the eye of continually advancing Truist s
- capabilities
- Exercise sound judgment and fosters 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
Analytics->Agile->Scrum->Cloud Services ( Azure + AWS+ IBM+ Oracle + snowflake + GCP)->Big Data->API - Integration
