Decision Scientist II

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Regular or Temporary:

Regular

Language Fluency: English (Required)

English

Work Shift:

1st shift (United States of America)

Please review the following job description:

Join the CX/OPEX Operational Excellence team as a Decision Scientist, where you’ll apply advanced analytics, statistical modeling, and business problem solving to drive measurable impact across the organization. In this highly visible individual contributor role, you’ll use an interdisciplinary approach—blending concepts from business strategy, applied statistics, mathematics, operations research, process design, information technology, and behavioral science—to deliver insights that enable leaders to make informed, data driven decisions.

You will work both independently and collaboratively with internal partners to analyze complex datasets, build scalable analytical solutions, and translate findings into clear, actionable recommendations that optimize business outcomes and support company goals. This role requires strong proficiency in SAS and Python, with the opportunity to deepen your technical expertise while influencing key business initiatives.

***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 (including, but not limited to H-1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN-1 or TN-2, E-3, O-1, or future sponsorship for U.S. lawful permanent residence status.)***

ESSENTIAL DUTIES AND RESPONSIBILITIES

Following is a summary of the essential functions for this job. Other duties may be performed, both major and minor, which are not mentioned below. Specific activities may change from time to time.

• As a Decision Scientist, focus on high impact, visible analyses and initiatives across multiple business models, covering banking channels, segments, and products.

• Partner on target initiatives as assigned; work independently and with internal teammates to drive decision science projects leveraging quantitative analysis techniques, including machine learning, in pursuit of business optimization and impact.

• Pursue business outcomes valued through increased revenue and/or efficiency leveraging data-driven insights powered by analytics in support of enhanced decision-making. Focus on continuous improvement in decision science delivery and outcomes in pursuit of business optimization.

• Explore and apply tools to solve business challenges and deliver solutions that are timely, accurate, and repeatable.

• Exercise sound judgment, risk management, and foster a client centric culture throughout design, development, and deployment practices.

• Foster communication and partnership across multiple levels of the organization including engagement with LOB contributors and junior-level managers.

QUALIFICATIONS

Required Qualifications:

The requirements listed below are representative of the knowledge, skill and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

• The incumbent must demonstrate a combination of academic aptitude, quantitative skills, business acumen, working knowledge of transaction processing application software, application processing systems, and collection inventory systems, strategic and creative thinking, and excellent written and verbal communications skills

• Bachelor’s degree or equivalent education and 3+ years of experience in Banking, Finance, Decision/Data Science, Analytics, Computer Science, Applied Mathematics or Engineering

• Must be able to perform in a cross-functional and collaborative team environment focused on supporting business partners with enhanced insights

• Innovative and strategic thinker with ability to connect to practical application, providing recommendations on target initiatives, with a strong bias to action and focus on quantifiable business impact

• Experience in delivering insights against tight deadlines in a collaborative environment to drive maximum impact

• Ability to maintain a high level of competency in statistical and analytical principles, tools, and techniques

• Incumbent should have an understanding of various database environments (IBM DB2, Oracle), technical programming skills (SAS, SQL, Toad), exposure to applied data science tools (R, Python, SAS E-Miner), familiarity with data visualizatio