Data Scientist I

About the Role

• Company: Truist
• Job Title: Data Scientist I
• Employment Type: Regular
• Language Fluency: English (Required)
• Work Shift: 1st shift (United States of America)

Key Responsibilities

• Perform sophisticated analytics, including statistical and predictive analytics, and machine learning modeling, to provide actionable insights that improve business outcomes and minimize risk.
• Provide consultation to business leaders and stakeholders on leveraging analytics insights and building strategies around analytics.
• Independently perform sophisticated data analytics (classical econometrics, machine learning, neural networks, natural language processing) using structured and unstructured data.
• Produce compelling data visualizations to communicate insights and influence outcomes among stakeholders.
• Take accountability for end-to-end data science solution design, technical delivery, and measurable business outcomes.
• Engage in stakeholder meetings to identify business objectives and scope solution requirements.
• Write, document, and deploy custom code (e.g., in Python, SAS, R) to create predictive analytics applications with minimal guidance.
• Use, maintain, share, and collaborate through Truist internal code repositories.
• Research and advocate for the adoption of emerging methods and technologies in data science to advance Truist’s capabilities.
• Exercise sound judgment and foster a 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.

Requirements & Tech Stack

• Data Analysis & Modeling:
• Statistical methods (classical statistics, probability theory, econometrics, time-series, statistical tests)
• Linear algebra concepts (optimization, complex matrix operations, eigenvalue decompositions, principal components)
• Calculus/differential equations, understanding of stochastic processes
• Data cleansing and preparation methodologies (regex, filtering, indexing, interpolation, outlier treatment)
• Machine learning modeling
• Neural networks
• Natural language processing
• Data Extraction & Management:
• SQL
• JQuery
• Hadoop, Pig, Hive, and/or NoSQL
• Spark
• Programming & Development:
• Python
• SAS
• R
• Collaboration & Tools:
• Truist internal code repositories

Qualifications

• Required:
• Bachelor’s degree in a quantitative field (Finance, Mathematics, Analytics, Data Science, Computer Science, or Engineering), or equivalent education and related training.
• Zero to four years of experience in a quantitative field.
• Understanding of statistical methods.
• Familiarity with linear algebra concepts.
• Working knowledge of calculus/differential equations.
• Understanding of data cleansing and preparation methodologies.
• Strong familiarity with data extraction in various environments.
• Working knowledge of Hadoop, Pig, Hive, and/or NoSQL, Spark.
• Experience managing multiple projects with tight deadlines in a collaborative environment.
• Preferred:
• Master’s degree or PhD in a quantitative field (Finance, Mathematics, Analytics, Data Science, Computer Science, or Engineering).
• Four years of relevant work experience (if candidate lacks a graduate degree).
• Previous experience in the banking or fin-tech industry.

Other Job Requirements / Working Conditions

• Physical Demands: Sitting Constantly (More than 50% of the time).
• Sensory: Able to access and interpret client information from a computer; able to hear and speak with individuals in person and on the phone.
• Dexterity: Able to work standard office equipment, including PC keyboard and mouse, copy/fax machines, and printers.
• Availability: Able to work all scheduled hours, including overtime as directed by manager/supervisor and required by business need.
• Travel: Minimal and up to 10%.