Quantitative Analytics Tech Lead

Freddie Mac

13h • $144,000 - $216,000

About The Position

At Freddie Mac, our mission of Making Home Possible is what motivates us, and it’s at the core of everything we do. Since our charter in 1970, we have made home possible for more than 90 million families across the country. Continue your career journey where your work contributes to a greater purpose.
Position Overview:
Freddie Mac’s Enterprise Risk Division is currently seeking a Quantitative Analytics Tech Lead to join the Single Family Acquisition Credit Risk team. The Tech Lead will be responsible for oversight, planning, executing, and documenting risk assessment of sophisticated financial models, methods, credit policies related to SF acquisition. Provides innovative, detailed and practical solutions to an extensive range of challenging problems. Work on complex issues where analysis of situations or data requires an in-depth knowledge of the company.
Our Impact:
The SF Acquisition Credit Risk team provides independent assessments of material Single-Family acquisition credit risks, and using our robust business sense, collaboration and focused analytics, we support Freddie Mac’s balance of credit risk and mission objectives within the defined risk appetite.
Your Impact:
Ensuring analysis and framework used in the Single-Family (SF) acquisition and regulatory submission capture all risks appropriately
Assisting and advising senior management in their decision making by providing quantitative and analytical support
Providing risk assessments related to SF credit risk models, credit policies and underwriting quality controls
Monitoring emerging risks, market trend and external research to provide effective challenge to the SF business area

Requirements

• Doctorate degree plus 3 years of working experience (or Master's degree with 5 years of equivalent work experience) in quantitative finance, statistics or a related quantitative field of studies.
• Coursework or work experience applying predictive modeling techniques, valuation approaches, and risk measurements from finance, statistics, economics, mathematics, data science, and computer programming to large data sets. Qualifying coursework may include—but is not limited to—statistics, mathematical programming, optimization, machine learning, computational methods, design and analysis of algorithms, Bayesian methods, derivatives, and Monte Carlo methods/modeling.
• Coursework or work experience writing statistical and/or optimization programs to develop models and algorithms. Programming languages may include—but are not limited to—Python, R, SQL and SAS. Proficiency in programming languages such as Python, R, SAS
• Advanced degree in Economics, Statistics, Mathematics or related fields
• Experience with consumer credit risk models, scorecards, credit bureau data and model, swap analysis
• Ability to translate complex statistical models and methodologies into simple business terms
• Mortgage industry experience in risk management and risk analytics

Responsibilities

• Ensuring analysis and framework used in the Single-Family (SF) acquisition and regulatory submission capture all risks appropriately
• Assisting and advising senior management in their decision making by providing quantitative and analytical support
• Providing risk assessments related to SF credit risk models, credit policies and underwriting quality controls
• Monitoring emerging risks, market trend and external research to provide effective challenge to the SF business area

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level