Data Scientist

Job Description

Data Scientist I | Truist Financial Corporation

The Tone:
This is a full-time role at Truist Financial Corporation, working the 1st shift in the United States of America. Truist focuses on financial products and services, leveraging data science to drive business improvements and mitigate risk. This specific role involves applying advanced analytical techniques, from classical econometrics to machine learning and natural language processing, across diverse data environments. As a Data Scientist I, you will be instrumental in translating complex data into actionable insights, providing strategic consultation to business leaders, and continuously advancing the company’s analytical capabilities through research and adoption of new technologies.

The TL;DR
• Role: Full Time
• Type: 1st shift
• Location: USA

• Mission: This role designs, delivers, and ensures measurable business outcomes from end-to-end data science solutions using sophisticated analytics.
• Tech Stack: Python, SAS, R, SQL, JQuery, Hadoop, Pig, Hive, NoSQL, Spark

What You’ll Actually Do
• Analytics Execution: Independently perform sophisticated data analytics, including econometrics, machine learning, neural networks, and natural language processing, using structured and unstructured data.
• Insight Communication: Produce compelling data visualizations to effectively communicate insights and influence outcomes across various stakeholders.
• Solution Ownership: Take accountability and ownership of the end-to-end data science solution design, technical delivery, and measurable business outcome.
• Code Development & Deployment: With minimal guidance, write, document, and deploy custom code in various environments (Python, SAS, R) to create predictive analytics applications.
• Capability Advancement: Actively research and advocate for the adoption of emerging methods and technologies in data science to continually advance Truist’s analytics capabilities.

The Must-Haves
• Background: Bachelor’s degree in a quantitative field such as Finance, Mathematics, Analytics, Data Science, Computer Science, or Engineering, or equivalent education and related training.
• Experience: Zero to four or more years of experience in a quantitative field, including managing multiple projects with tight deadlines in a collaborative environment, and experience with data extraction in various environments (SQL, JQuery).
• Skills: Strong understanding of statistical methods (classical statistics, probability theory, econometrics, time-series, primary statistical tests); familiarity with linear algebra concepts (optimization, matrix operations, eigenvalue decompositions, principal components) and working knowledge of calculus/differential equations and stochastic processes; understanding of data cleansing and preparation methodologies (regex, filtering, indexing, interpolation, outlier treatment); working knowledge of Hadoop, Pig, Hive, and/or NoSQL, Spark.
• Bonus: 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.