Client Quantitative Analyst I: Data Analytics & Insights

Bank of America; Charlotte (TX); On-site; USD 90,000 - 120,000; Full time

Job summary

United States Digital Space LLC is seeking a Client Quantitative Analyst to support analytical work for financial services projects. You will leverage databases to acquire client and performance data, transform it into meaningful insights, and present findings to leaders to guide business decisions.

The role requires experience with SQL, SAS, Python, Spark/Scala, and the ability to translate complex data into clear recommendations for non-technical partners.

Qualifications

• Bachelor's Degree or higher in finance, math/statistics, computer science, or a quantitative field.
• 2+ years of experience in applied data science or quantitative research.
• Experience with Hadoop or similar big data platforms.
• Ability to translate data into actionable business insights.
• Strong written and verbal communication for non-technical audiences.

Responsibilities

• Support analytical work efforts across projects within a line of business.
• Leverage databases to acquire client and performance data and transform it into insights.
• Deliver insights to leaders to inform complex business decisions.
• Communicate complex data outputs clearly to business partners using PowerPoint, Excel, Tableau.
• Collaborate with partners to coordinate priorities and maintain data quality.

Skills

Data Analytics

Data Mining

Analytical Thinking

Data Visualization

Business Intelligence

Data Quality Management

Continuous Improvement

Innovative Thinking

Education

Bachelor’s degree in finance/math/statistics/CS

Master’s degree (desired)

Tools

SQL

Python

Spark/Scala

Tableau

Hadoop

PowerPoint

Excel

Job description

United States Digital Space LLC is seeking a Client Quantitative Analyst to support analytical work for financial services projects. You will leverage databases to acquire client and performance data, transform it into meaningful insights, and present findings to leaders to guide business decisions.

The role requires experience with SQL, SAS, Python, Spark/Scala, and the ability to translate complex data into clear recommendations for non-technical partners.