Data Science Manager

Veritas Partners; McLean (VA); On-site; USD 180,000 - 240,000; Full time

Job summary

Veritas Partners in McLean, VA seeks a Senior Manager of Data Science to lead the decision science team and own the NPV modeling function for consumer banking products.

You will manage a team of data scientists, develop CLTV modeling to drive member profitability, and develop pricing and underwriting models to support lending decisions. Strong leadership and advanced analytics are essential.

Qualifications

• Bachelor's degree required; Master's or PhD preferred.
• Ten years of experience building statistical models.
• Experience managing others.
• Advanced SQL, Python, and R skills required.
• Experience in building risk, revenue and targeting models.
• Strong analytical and tactical thinking.

Responsibilities

• Manage a team of data scientists to develop, maintain, and enhance NPV models for consumer banking products.
• Build CLTV modeling to drive member profitability.
• Develop and implement acquisition pricing and credit underwriting models to support lending decisions.
• Develop statistical models and scorecards for credit underwriting, loan pricing, collection, and portfolio risk monitoring.
• Develop price elasticity models to support risk-adjusted pricing.
• Monitor performance of quantitative models and support independent model validation efforts.
• Utilize credit models and analytics to assist lending with policies and strategies.

Skills

SQL

Python

R

Statistical modeling

People management

Critical thinking

Education

Bachelor's degree

Master's/PhD preferred

Job description

Our client, a financial services firm in McLean, VA, is currently seeking a Senior Manager of Data Science to join their team. The incumbent will manage a team and lead the NPV modeling function within the decision science department.

Responsibilities

• Manage a team of data scientists to develop, maintain, and enhance NPV models for consumer banking products
• Build Customer Life Time Value (CLTV) modeling to drive member profitability
• Develop and implement acquisition pricing and credit underwriting models to support lending decisions
• Develop statistical models and scorecards for credit underwriting, loan pricing, collection, and portfolio risk monitoring
• Develop price elasticity models to support risk adjusted pricing
• Monitor performance of quantitative models and support independent model validation efforts
• Utilize credit models and analytics to assist lending with policies and strategies

Qualifications

• Bachelor's degree is required
• Master's and/or PHD is preferred
• Ten years of experience building statistical models
• Experience managing others
• Advanced SQL, Python, and R skills required
• Experience in building risk, revenue and targeting models
• Critical thinking using both analytical and tactical approach