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Lead Quantitative Modeler

Fannie Mae

Full-time
USA
$135k-$176k per year
python
machine learning
risk management
computer science
The job listing has expired. Unfortunately, the hiring company is no longer accepting new applications.

To see similar active jobs please follow this link: Remote Development jobs

Job Description

As a valued colleague on our team, you will be responsible for leveraging expertise in economics, statistics (with a focus on time-series modeling), and advanced machine learning techniques (including reinforcement learning) to develop predictive models, optimize risk management strategies, and drive actionable insights. You will also act as team lead while conducting theoretical and empirical research with public and proprietary data in all areas of the mortgage finance business. This may include mortgage products and securities, borrower behavior, investment and hedging strategies, residential property valuation, macroeconomic models, including housing prices and interest rate, financial valuation of finance assets and derivatives, economic capital, and stress testing. Additionally, you will coach and mentor team members.

THE IMPACT YOU WILL MAKE
The Lead Quantitative Modeler role will offer you the flexibility to make each day your own, while working alongside people who care so that you can deliver on the following responsibilities:

  • Lead the development and implementation of loan performance modeling frameworks, methodologies, and algorithms to predict borrower behavior, loan defaults, prepayments, and delinquencies.
  • Conduct in-depth analysis of economic indicators, market trends, and macroeconomic factors to inform modeling assumptions, parameter estimates, and scenario analysis.
  • Design and implement statistical models and time series forecasting techniques to analyze historical loan performance data, identify patterns, and forecast future trends.
  • Apply advanced machine learning algorithms, including reinforcement learning techniques, to optimize risk management strategies, automate decision-making processes, and improve model performance.
  • Collaborate closely with cross-functional teams, including data scientists, economists, risk managers, and business stakeholders, to gather requirements, define project scope, and drive model development efforts.
  • Develop and maintain documentation, code repositories, and model validation reports in compliance with regulatory requirements and internal policies.
  • Stay current with emerging trends, methodologies, and best practices in quantitative finance, econometrics, statistics, and machine learning, and apply them to enhance modeling capabilities and stay ahead of the curve.


Qualifications

THE EXPERIENCE YOU BRING TO THE TEAM

Minimum Requirements:

  • 4 years of proven experience in developing and implementing predictive models.
  • Bachelor’s degree in economics, Statistics, Computer Science, or a related quantitative field.

Desired Experiences:

  • Advanced degree in Economics, Statistics, Computer Science, or a related quantitative field.
  • Experience with time series analysis techniques and advanced machine learning algorithms in a quantitative finance or risk management environment.
  • Proficiency in programming languages such as Python, or R, and experience with relevant libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
  • Strong understanding of econometric principles, statistical methodologies, and quantitative modeling techniques, with a focus on time series analysis, stochastic processes, and Bayesian inference.
  • Experience with loan performance modeling, credit risk assessment, and portfolio optimization in the financial services industry is highly desirable.
  • Excellent analytical, problem-solving, and communication skills, with the ability to translate complex technical concepts into actionable insights for non-technical stakeholders.
  • Proven ability to work collaboratively in a cross-functional team environment, manage multiple projects simultaneously, and deliver high-quality results under tight deadlines.


Additional Information

The future is what you make it to be. Discover compelling opportunities at careers.fanniemae.com.

Fannie Mae is an Equal Opportunity Employer, which means we are committed to fostering a diverse and inclusive workplace. All qualified applicants will receive consideration for employment without regard to race, religion, national origin, gender, gender identity, sexual orientation, personal appearance, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation in the application process, email us at careers_mailbox@fanniemae.com. #LI-ME1

 

The hiring range for this role is set forth on each of our job postings located on Fannie Mae's Career Site. Final salaries will generally vary within that range based on factors that include but are not limited to, skill set, depth of experience, certifications, and other relevant qualifications. This position is eligible to participate in a Fannie Mae incentive program (subject to the terms of the program). As part of our comprehensive benefits package, Fannie Mae offers a broad range of Health, Life, Voluntary Lifestyle, and other benefits and perks that enhance an employee’s physical, mental, emotional, and financial well-being. See more here.

About the job

Full-time
USA
$135k-$176k per year
Posted 1 year ago
python
machine learning
risk management
computer science
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Lead Quantitative Modeler

Fannie Mae
The job listing has expired. Unfortunately, the hiring company is no longer accepting new applications.

To see similar active jobs please follow this link: Remote Development jobs

Job Description

As a valued colleague on our team, you will be responsible for leveraging expertise in economics, statistics (with a focus on time-series modeling), and advanced machine learning techniques (including reinforcement learning) to develop predictive models, optimize risk management strategies, and drive actionable insights. You will also act as team lead while conducting theoretical and empirical research with public and proprietary data in all areas of the mortgage finance business. This may include mortgage products and securities, borrower behavior, investment and hedging strategies, residential property valuation, macroeconomic models, including housing prices and interest rate, financial valuation of finance assets and derivatives, economic capital, and stress testing. Additionally, you will coach and mentor team members.

THE IMPACT YOU WILL MAKE
The Lead Quantitative Modeler role will offer you the flexibility to make each day your own, while working alongside people who care so that you can deliver on the following responsibilities:

  • Lead the development and implementation of loan performance modeling frameworks, methodologies, and algorithms to predict borrower behavior, loan defaults, prepayments, and delinquencies.
  • Conduct in-depth analysis of economic indicators, market trends, and macroeconomic factors to inform modeling assumptions, parameter estimates, and scenario analysis.
  • Design and implement statistical models and time series forecasting techniques to analyze historical loan performance data, identify patterns, and forecast future trends.
  • Apply advanced machine learning algorithms, including reinforcement learning techniques, to optimize risk management strategies, automate decision-making processes, and improve model performance.
  • Collaborate closely with cross-functional teams, including data scientists, economists, risk managers, and business stakeholders, to gather requirements, define project scope, and drive model development efforts.
  • Develop and maintain documentation, code repositories, and model validation reports in compliance with regulatory requirements and internal policies.
  • Stay current with emerging trends, methodologies, and best practices in quantitative finance, econometrics, statistics, and machine learning, and apply them to enhance modeling capabilities and stay ahead of the curve.


Qualifications

THE EXPERIENCE YOU BRING TO THE TEAM

Minimum Requirements:

  • 4 years of proven experience in developing and implementing predictive models.
  • Bachelor’s degree in economics, Statistics, Computer Science, or a related quantitative field.

Desired Experiences:

  • Advanced degree in Economics, Statistics, Computer Science, or a related quantitative field.
  • Experience with time series analysis techniques and advanced machine learning algorithms in a quantitative finance or risk management environment.
  • Proficiency in programming languages such as Python, or R, and experience with relevant libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
  • Strong understanding of econometric principles, statistical methodologies, and quantitative modeling techniques, with a focus on time series analysis, stochastic processes, and Bayesian inference.
  • Experience with loan performance modeling, credit risk assessment, and portfolio optimization in the financial services industry is highly desirable.
  • Excellent analytical, problem-solving, and communication skills, with the ability to translate complex technical concepts into actionable insights for non-technical stakeholders.
  • Proven ability to work collaboratively in a cross-functional team environment, manage multiple projects simultaneously, and deliver high-quality results under tight deadlines.


Additional Information

The future is what you make it to be. Discover compelling opportunities at careers.fanniemae.com.

Fannie Mae is an Equal Opportunity Employer, which means we are committed to fostering a diverse and inclusive workplace. All qualified applicants will receive consideration for employment without regard to race, religion, national origin, gender, gender identity, sexual orientation, personal appearance, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation in the application process, email us at careers_mailbox@fanniemae.com. #LI-ME1

 

The hiring range for this role is set forth on each of our job postings located on Fannie Mae's Career Site. Final salaries will generally vary within that range based on factors that include but are not limited to, skill set, depth of experience, certifications, and other relevant qualifications. This position is eligible to participate in a Fannie Mae incentive program (subject to the terms of the program). As part of our comprehensive benefits package, Fannie Mae offers a broad range of Health, Life, Voluntary Lifestyle, and other benefits and perks that enhance an employee’s physical, mental, emotional, and financial well-being. See more here.

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