Senior Quantitative Analyst - AI-Driven Data & Risk

Federal Reserve Bank of Minneapolis; Philadelphia (Philadelphia County); On-site; USD 100,000 - 160,000; Full time

Benefits offered by this job

Medical insurance

Prescription coverage

Dental coverage

Vision insurance

401k plan

Pension plan

Vacation/Sick time & holidays

Commuter allowance

Flex benefits

Job summary

The Federal Reserve Bank of Philadelphia is seeking a quantitative analyst in the RADAR Data Warehouse team within the SRC Department. You will serve as a data subject matter expert and manage data through its lifecycle, onboarding new data and delivering high-quality datasets for economists and analysts.

A key focus is applying Artificial Intelligence to enhance data management and analytics across datasets and projects.

Qualifications

• Bachelor’s in business or quantitative fields; advanced degree preferred.
• Minimum five years in banking, bank supervision, or finance-related field for higher grade.
• Experience with econometric software (R, Python) and analytical tools (SQL/Tableau).

Responsibilities

• Onboard new data and maintain data changes with stakeholders.
• Establish data quality checks and resolve data issues.
• Conduct advanced analytics for various projects.
• Provide data and analytics SME support to economists and analysts.
• Create and maintain user-facing data products and tools.
• Lead data/tech training events and engage with business lines.

Skills

R/Python

SQL

Tableau

Databricks

Cloud AWS

Data management

Education

Bachelor's degree in business or quantitative fields

Advanced degree preferred

Tools

Databricks

Collibra

Starburst

AWS

Job description

The Federal Reserve Bank of Philadelphia is seeking a quantitative analyst in the RADAR Data Warehouse team within the SRC Department. You will serve as a data subject matter expert and manage data through its lifecycle, onboarding new data and delivering high-quality datasets for economists and analysts.

A key focus is applying Artificial Intelligence to enhance data management and analytics across datasets and projects.