Data Scientist

• Perform sophisticated data analytics, including statistical analytics, predictive analytics, machine learning, neural networks, natural language processing, and econometrics
• Use structured and unstructured data across a variety of environments
• Produce compelling data visualizations to communicate insights and influence stakeholder outcomes
• Own end-to-end data science solution design, technical delivery, and measurable business outcomes
• Engage stakeholders to identify business objectives and scope solution requirements
• Write, document, and deploy custom code in Python, SAS, R, and other environments to create predictive analytics applications
• Use, maintain, share, and collaborate through Truist internal code repositories
• Research and advocate adoption of emerging data science methods and technologies
• Apply sound judgment and risk management throughout design, development, and deployment
• Partner with cross-functional teams on data usage rules, data governance, and analytics capabilities

Data Scientist I

• Champion Artificial Intelligence and Data Science adoption across the Nuclear Engineering organization
• Drive AI-enabled strategies toward the $800M EBITDA growth goal by 2028
• Lead the Engineer 2030 transformation to double engineering productivity from $2M to $4M per engineer per year
• Lead a high-performing team developing and implementing AI-enabled capabilities across the nuclear enterprise
• Collaborate with Digital Engineering to ensure regulatory compliance and alignment with digital tools strategy and roadmap
• Challenge the status quo and identify waste using Lean and AI thinking
• Partner with Digital Technology and Advanced Research to evolve the ML/AI strategy
• Create standard work ensuring AI initiatives meet nuclear-business regulatory and security requirements
• Apply Plan, Do, Check, Act methodology to improve standard work and drive continuous improvement
• Own technical requirements and key performance indicators for AI initiatives
• Drive measurable business impact and timely problem-solving

Nuclear Engineering Lead – AI, Data Science

• Design, develop and validate machine learning and predictive analytics-based solutions supporting the U.S. Commercial function
• Evaluate business and analytical needs and select and implement appropriate statistical, machine learning, and AI methodologies
• Follow and refine best practices for model development, monitoring, governance, and continuous improvement
• Develop and deploy advanced analytics, machine learning, and AI solutions generating insights into patient populations, healthcare provider behavior, treatment patterns, and disease progression
• Develop predictive models supporting patient identification, segmentation, treatment initiation, adherence, persistence, and healthcare provider engagement strategies
• Integrate and analyze claims, electronic health records, specialty pharmacy, and commercial data
• Partner with Commercial, Medical Affairs, and Insights & Analytics teams to translate insights into evidence-based business strategies
• Communicate complex analytical findings to leadership and cross-functional teams
• Support a culture of innovation, collaboration, continuous learning, and technical excellence
• Manage external vendors and consulting partners
• Manage multiple initiatives while ensuring timely and high-quality execution
• Report to the Director, Predictive Sciences

Senior Data Science Manager, Predictive Analytics – AI

• Design and implement scalable data architectures and data models for enterprise reporting, analytics, and business intelligence
• Design, develop, and optimize ETL/ELT pipelines and workflows for large-scale datasets
• Develop data solutions using SQL and Python to transform, validate, and analyze complex datasets
• Manage and provide technical leadership for a global team of Data Engineers and Business Analysts
• Prioritize tasks, conduct code reviews, and support professional development while enforcing engineering best practices
• Serve as a primary escalation point for complex data issues and maintain high data reliability
• Architect and support data warehousing solutions using platforms such as Oracle, SQL Server, Amazon Redshift, and Snowflake
• Develop data pipelines and historical data tracking structures such as Slowly Changing Dimensions
• Establish and enforce data governance, data quality standards, and audit controls
• Support enterprise financial and operational reporting through data processing, validation, and reconciliation
• Partner with cross-functional stakeholders to translate business requirements into scalable technical solutions
• Contribute to data frameworks and processes supporting planning, forecasting, and evolving business needs

Manager, Data Information, Global

• Analyze and interpret large datasets to identify revenue generation opportunities and develop risk management strategies
• Perform business analytics, including data analysis, trend identification, pattern recognition, machine learning, text mining, and statistical analysis
• Apply agile practices to project management, solution development, deployment, and maintenance
• Create and maintain technical documentation for business requirements, specifications, analytical solutions, and production implementation
• Manage quantitative models, data science products, data analysis reports, and data visualizations
• Present technical concepts and analysis results to internal stakeholders
• Identify potential issues and develop controls to mitigate risk
• Research advances in data science and artificial intelligence
• Contribute to development and maintenance of the THOR information product
• Use SQL and analytical tools to investigate transaction data, identify anomalies, support value-added attributes, and validate production changes
• Build knowledge of THOR database structures, data sources, attributes, and production processes
• Support product enhancement analysis, quality control, testing, documentation, and post-production validation
• Investigate and communicate data anomalies, risks, questions, and opportunities
• Evaluate approaches for transaction categorization and THOR attributes
• Support ad hoc analytical requests, user documentation, training materials, and presentations
• Collaborate with team members and cross-functional partners to resolve data and development issues

• Analyze and interpret large datasets to uncover potential revenue generation opportunities and develop risk management strategies
• Collaborate with stakeholders to understand business problems and devise data-driven solutions
• Perform business analytics, including data analysis, trend identification, and pattern recognition, using machine learning, text mining, and statistical analysis
• Apply Agile practices for project management, solution development, deployment, and maintenance
• Develop, test, and deploy data science, machine learning, and AI-driven solutions
• Create and maintain technical documentation covering business requirements, specifications, and production implementation
• Manage multiple priorities and deliver quantitative models, data science products, data analysis reports, and data visualizations
• Present technical concepts and analysis results to internal stakeholders through in-person and virtual conversations
• Develop professional relationships and collaborate across Global Risk Analytics, Global Technology, Global Compliance & Operational Risk, and other business teams
• Identify potential issues and develop controls to mitigate risk
• Research advances in data science and artificial intelligence
• Support automation, analytics, modeling, model governance, and innovative solutions across risk, compliance, and technology domains

• Analyze and interpret large datasets to identify revenue generation opportunities and develop risk management strategies
• Collaborate with stakeholders to understand business problems and devise analytical solutions
• Perform business analytics, including data analysis, trend identification, and pattern recognition, using machine learning, text mining, and statistical analysis
• Apply agile practices for project management, solution development, deployment, and maintenance
• Create and maintain technical documentation for business requirements, specifications, and production implementation
• Manage quantitative models, data science products, data analysis reports, and data visualizations while maintaining quality and timeliness
• Present technical concepts and analysis results to diverse internal stakeholders
• Identify potential issues and develop controls to mitigate risk
• Research advances in data science and artificial intelligence
• Support AI and model development across the full product lifecycle, from ideation through retirement, across multiple lines of business
• Work with senior model owners, developers, and users to streamline manual processes, improve decision-making, and deliver scalable, compliant solutions
• Identify opportunities to reuse existing AI technologies, models, and methodologies and share best practices
• Support Bank of America's Enterprise AI Catalyst program and AI enablement strategy

• Analyze and interpret large datasets to uncover potential revenue generation opportunities and develop risk management strategies
• Perform business analytics including data analysis, trend identification, and pattern recognition using machine learning, text mining, and statistical analysis
• Apply agile practices to project management, solution development, deployment, and maintenance
• Create and maintain technical documentation covering business requirements, specifications, and production implementation
• Manage multiple priorities and deliver quantitative models, data science products, data analysis reports, and data visualizations with quality and timeliness
• Present technical concepts and analysis results to diverse internal stakeholders in person and virtually
• Build professional relationships and collaborate with stakeholders, senior model owners, developers, and users across lines of business
• Identify potential issues and develop controls to mitigate risk
• Research advances in data science and artificial intelligence
• Support AI and model development across the full product lifecycle, from ideation through retirement
• Streamline manual processes, improve decision-making, and deliver scalable, compliant, integrated solutions
• Identify opportunities to leverage existing AI technologies, models, and methodologies to avoid duplication, promote reuse, and share best practices
• Support Bank of America's Enterprise AI Catalyst program and AI enablement strategy

• Analyze and interpret large datasets to identify revenue generation opportunities and develop risk management strategies
• Collaborate with stakeholders to understand business problems and devise data-driven solutions
• Perform business analytics, data analysis, trend identification, and pattern recognition using machine learning, text mining, and statistical analysis
• Apply Agile practices to project management, solution development, deployment, and maintenance
• Create and maintain technical documentation for business requirements, specifications, and production implementation
• Manage multiple priorities and deliver quantitative models, data science products, data analysis reports, and data visualizations
• Present technical concepts and analysis results to diverse internal stakeholders
• Identify potential issues and develop controls to mitigate risk
• Research advances in data science and artificial intelligence
• Support the development, testing, and deployment of data science, machine learning, and AI-driven solutions across risk, compliance, and technology organizations

• Analyze and interpret large datasets to uncover revenue generation opportunities and develop risk management strategies
• Perform business analytics, including data analysis, trend identification, and pattern recognition using machine learning, text mining, and statistical analysis
• Apply agile practices for project management, solution development, deployment, and maintenance
• Create and maintain technical documentation for analytical solutions and production implementation
• Manage quantitative models, data science products, data analysis reports, and data visualizations
• Present technical concepts and analysis results to internal stakeholders
• Identify potential issues and develop controls to mitigate risk
• Research advances in data science and artificial intelligence
• Contribute to development and maintenance of the THOR information product
• Use SQL and analytical tools to investigate transaction data, identify anomalies, support value-added attributes, and validate production changes
• Support analysis and evaluation of proposed product enhancements and production releases
• Apply quality-control practices across analysis, development, testing, documentation, and post-production validation
• Investigate data anomalies and communicate findings, risks, and opportunities
• Evaluate transaction categorization and other THOR value-added attributes
• Support ad hoc analytical requests, user documentation, training materials, and informational presentations
• Collaborate with team members and cross-functional partners to resolve data or development issues