What are the responsibilities and job description for the Data Architect - Artificial Intelligence And Machine Learning Engineer position at Truist?
Company Description
Truist Financial Corporation is a purpose-driven financial services company dedicated to improving lives and building stronger communities. Headquartered in Charlotte, North Carolina, Truist is one of the top-10 commercial banks in the United States, holding total assets of $535 billion as of March 31, 2024. Truist offers a broad portfolio of financial services, including consumer banking, wealth management, corporate banking, and specialized lending. With a strong presence in high-growth markets, the company provides innovative solutions to meet client needs and drive sustainable success. Learn more at Truist.com.
Role Description
This is a full-time, on-site role for a Data Architect - Artificial Intelligence and Machine Learning Engineer, based in one of our 4 core hub locations: Charlotte, NC; Atlanta, GA; Raleigh, NC or Richmond, VA. The individual in this role will design, develop, and optimize data architectures, pipelines, and systems to support artificial intelligence (AI) and machine learning (ML) applications. Responsibilities include analyzing data requirements, building scalable solutions, implementing predictive models, and ensuring data quality. Collaboration with cross-functional teams to align data strategies with business goals and fostering innovation in data-driven initiatives will be a vital part of this role.
Qualifications
1. Bachelor's degree and 8 years of experience in a quantitative field such as Finance, Mathematics, Analytics, Data Science, Computer Science, or Engineering.
2. Demonstrated knowledge and skill in strategic data assets warehousing and transactional application data concepts and technology.
3. Proven experience with data engineering and ability to manage large data volumes.
4. Demonstrate understanding of data analytics life cycle methodologies including data cleansing and preparation methodologies
5. Strong familiarity with data extraction in a variety of environments (e.g., SQL, SAS, etc.).
6. Experience in managing multiple projects with tight deadlines in a collaborative environment.
7. Maintain a high level of competency in analytical principles, tools, and techniques