Data Scientist I - Card Fraud

Data Scientist I

We are seeking Data Scientist I to support card fraud and token provisioning initiatives, with a focus on digital payment security across mobile and digital wallet platforms (e.g., Apple Pay, Google Pay, Samsung Pay, and merchant tokenization). This role will contribute to detecting, analyzing, and mitigating fraud risk while supporting secure transaction experiences. The ideal candidate will bring experience in card fraud, digital fraud, or related risk domains, along with strong technical skills in SAS, SQL, and programming for data analysis and modeling. Exposure to tokenization or digital wallet technologies is preferred but not required.

For this opportunity, Truist will not sponsor an applicant for work visa status or employment authorization, nor will we offer any immigration-related support for this position.

Essential Duties and Responsibilities:

• Independently perform sophisticated data analytics (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 outcome.
• 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.

Required Qualifications:

• Bachelor's degree and zero to 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
• Exhibit understanding of statistical methods, including a broad understanding of 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, with understanding of stochastic processes
• Demonstrate understanding of data cleansing and preparation methodologies, including regex, filtering, indexing, interpolation, and outlier treatment
• Strong familiarity with data extraction in a variety of environments (SQL, JQuery, etc.)
• Working knowledge of Hadoop, Pig, Hive, and/or NoSQL, Spark
• Experience in managing multiple projects with tight deadlines in a collaborative environment

Preferred Qualifications:

• Master's degree or PhD in quantitative fields such as Finance, Mathematics, Analytics, Data Science, Computer Science, or Engineering
• Four years of relevant work experience if candidate lacks graduate degree
• Previous experience in the banking or fin-tech industry

Truist is an Equal Opportunity Employer that does not discriminate on the basis of race, gender, color, religion, citizenship or national origin, age, sexual orientation, gender identity, disability, veteran status, or other classification protected by law. Truist is a Drug Free Workplace.