Data Scientist II – Fair Banking and Regulatory Programs

• Perform sophisticated data analytics using classical econometrics, machine learning, neural networks, and natural language processing
• Work with structured and unstructured data in a variety of environments
• Produce data visualizations to communicate insights and influence stakeholder outcomes
• Own end-to-end data science solution design, technical delivery, and measurable business outcomes
• Participate in stakeholder meetings to identify business objectives and scope solution requirements
• Write, document, and deploy custom code in Python, SAS, R, and other environments
• 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 risk management practices throughout design, development, and deployment
• Partner with cross-functional teams on data usage rules, data governance, and analytics capabilities
• Serve as data expert and liaison with Business Unit data teams
• Collaborate with model development teams during development activities
• Consult with business leaders and stakeholders on leveraging analytics insights and developing analytics strategies
• Test and assess compliance with ECOA, FHA, UDAAP, HMDA, and 1071 regulations

• Bachelor's degree and four or more years of experience in a quantitative field such as Finance, Mathematics, Analytics, Data Science, Computer Science, or Engineering, or equivalent education and related training
• Understanding of statistical methods, including classical statistics, probability theory, econometrics, time-series, and primary statistical tests
• Familiarity with linear algebra concepts for optimization, complex matrix operations, eigenvalue decompositions, and principal components
• Working knowledge of calculus/differential equations and understanding of stochastic processes
• Understanding of data cleansing and preparation methodologies, including regex, filtering, indexing, interpolation, and outlier treatment
• Strong familiarity with data extraction in environments such as SQL and JQuery
• Working knowledge of Hadoop, Pig, Hive, No
  
  SQL, and Spark
• Experience managing multiple projects with tight deadlines in a collaborative environment
• English language fluency required
• Ability to work all scheduled hours, including overtime as directed
• Master's degree or PhD in a quantitative field preferred
• Fair lending or credit risk experience preferred
• Previous banking or fintech industry experience preferred

Demonstrates expertise in data analytics, including classical econometrics, machine learning, and natural language processing, while effectively communicating insights through data visualizations. Proficient in Python, SAS, R, and SQL, with a strong understanding of statistical methods and data governance practices.

• Data Analytics
• Machine Learning
• Python Programming
• Statistical Methods
• Data Governance

• Econometrics
• Natural Language Processing
• Data Visualization
• Predictive Analytics
• Data Cleansing
• Statistical Tests
• Linear Algebra
• Calculus
• SQL
• Hadoop

• Collaboration
• Stakeholder Engagement
• Project Management

• Fair Lending
• Credit Risk
• Banking
• Fintech
• ECOA
• FHA
• UDAAP
• HMDA
• 1071 Regulations

• SAS
• R
• JQuery
• No
  
  SQL
• Spark
• Pig
• Hive
• Truist Internal Code Repositories