Truist is looking to solve business problems related to fraud prevention by applying advanced analytics and innovative technologies to protect customers and drive business impact.
Requirements
- 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 with real-time decisioning platforms or fraud tools.
- Knowledge of payment networks, issuer/acquirer processes, or financial services regulations.
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.
- Independently 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 Truists capabilities.
Other
- Bachelors 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
- Experience in managing multiple projects with tight deadlines in a collaborative environment
- Masters degree or PhD in a quantitative field 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
