Perform sophisticated analytics (statistical and predictive analytics, machine learning modeling, etc.) to provide actionable insights that improve business outcomes and minimize risk. Provide consultation to business leaders and other stakeholders on how to leverage analytics insights and build strategies around analytics. Lead small projects with manageable risks and resource requirements; play significant roles in larger, more complex initiatives. Act as a resource for teammates with less experience. 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. Perform sophisticated data analytics (encompassing data mining, inferential statistical analysis, and predictive analytics, for example) on structured and unstructured data. Identify actionable insights from various (or multiple) sources of data that measurably improve business outcomes or reduce business risk. 2. Support new, ongoing, and strategic projects and take accountability and ownership of end-to-end data science solution design, technical delivery, and measurable business outcome. 3. Extract and evaluate information gathered from multiple sources, resolve data conflicts and customize communication of key data findings, while providing recommendations to diverse audiences. 4. Provide analytical consulting and thought leadership to various business areas and fosters strategic and positive relationship with business partners. 5. Co-design the optimal solutions to solve the complex business problems with advanced data science capabilities to create business value. Emphasize reusability and scalability in all design, development, deployment and mentoring activities through implementing consistent coding standards and best practices, focusing on clarity of communication across stakeholder groups and maintaining rigorous documentation. 6. 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; help with the overall risk management for the team. 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.
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Job Type
Full-time
Career Level
Mid Level
Number of Employees
5,001-10,000 employees