Decision Scientist II: Banking Analytics & Insights

Truist Financial; Charlotte (NC); On-site; USD 90,000 - 140,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

Life insurance

Disability insurance

401k plan

Paid vacation

Job summary

Truist Financial is seeking an experienced Decision Scientist to support analytics projects across banking channels, segments, and products. You will work independently and with teams to generate insights that drive quantifiable improvements in revenue and efficiency, leveraging machine learning and various data tools.

Ideal candidates have strong quantitative skills, cross-functional collaboration experience, and proficiency with SAS, SQL, Python and BI tools.

Qualifications

• Combination of quantitative skills, business acumen and strong communication abilities.
• Experience with transaction processing systems and data science tooling.
• Familiarity with data visualization and BI tools and general programming knowledge.

Responsibilities

• Lead high-impact analyses across banking channels, segments and products.
• Partner on initiatives using quantitative techniques including machine learning.
• Deliver data-driven insights to drive revenue and efficiency.
• Apply tools to solve business challenges with timely, accurate, repeatable solutions.
• Collaborate across organization levels and strengthen decision science delivery.

Skills

Quantitative skills

Business acumen

Written and verbal communication

Analytical thinking

Cross-functional collaboration

Education

Bachelor's degree or equivalent

Master's degree preferred

Tools

SAS

SQL

Toad

IBM DB2

Oracle

R

Python

Snowflake

Tableau

Power BI

Excel

PowerPoint

Word

Job description

Truist Financial is seeking an experienced Decision Scientist to support analytics projects across banking channels, segments, and products. You will work independently and with teams to generate insights that drive quantifiable improvements in revenue and efficiency, leveraging machine learning and various data tools.

Ideal candidates have strong quantitative skills, cross-functional collaboration experience, and proficiency with SAS, SQL, Python and BI tools.