Senior Model Risk Forecasting Specialist

BNY; Pittsburgh (Allegheny County); On-site; USD 120,000 - 160,000; Full time

Benefits offered by this job

Competitive compensation

Wellbeing programs

Paid volunteer time

401(k) plan

Job summary

Bank of New York Mellon (BNY) is seeking a Senior Specialist, Model Risk Developer to join the Modeling & Analytics team in Pittsburgh, PA or Lake Mary, FL. The role focuses on developing macroeconomic forecasting methodologies and supporting scenario execution with key partners.

The ideal candidate has a strong quantitative background, 2+ years in forecasting within finance, and proficiency in programming languages such as R and Python.

Qualifications

• Master's degree in a quantitative discipline is required; PhD is a plus.
• 2+ years in research/forecasting/business analytics in finance or similar.
• Experience in forecasting and macroeconomic/financial modeling is a plus.
• Strong programming and documentation skills with R/Python/EViews/Stata.
• Excellent organizational and communication skills; ability to meet deadlines.

Responsibilities

• Develop, enhance and document macroeconomic forecasting methodologies.
• Execute macroeconomic forecasts for scenarios working with vendors and partners.
• Manage inbound questions, deliverables and ad-hoc requests with timely delivery.
• Interact with downstream modelers and Finance, Treasury, Model Risk Management teams.
• Demonstrate strong interpersonal skills and ability to work in a multi-priority environment.
• Strong programming skills in R is desired.

Skills

Quantitative analysis

Macroeconomics

Forecasting

Programming

Communication

Education

Master's degree in quantitative field

PhD preferred

Tools

R

Python

EViews

Stata

Job description

Bank of New York Mellon (BNY) is seeking a Senior Specialist, Model Risk Developer to join the Modeling & Analytics team in Pittsburgh, PA or Lake Mary, FL. The role focuses on developing macroeconomic forecasting methodologies and supporting scenario execution with key partners.

The ideal candidate has a strong quantitative background, 2+ years in forecasting within finance, and proficiency in programming languages such as R and Python.