Quantitative Analytics Tech Lead

Freddie Mac•McLean, VA

13d

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. Join an organization where your work contributes to a greater purpose. Position Overview: Are you someone who thrives on applying quantitative analytics to influence business strategy and decision making? If you are passionate about developing new insights and motivated by the potential to advise key business decisions and strategy in the Single-Family Mortgage domain, then apply today and join our Single Family (SF) Business Analytics Team at Freddie Mac! Our Impact: Our team identifies and recommends new business mix optimization opportunities and influences key Single-Family stakeholders around actions to enhance balanced scorecard objectives with robust quantitative analytical skills. Your Impact: The work in the immediate group is focused on wide variety of interesting topics ranging from: Monitoring credit risk patterns of SF new fundings and proactively identify emerging risk by applying AI/Machine Learning techniques to advance analytics. Manage the GEO Intelligence Forum which stays on top of emerging macro and mortgage performance patterns across GEOs Apply sophisticated technical skills to provide deeper insights into credit risk trends using traditional and non-traditional mortgage data. Enhance analytical ability in the team by building subject matter expertise in risk models, statistical methods, credit policy, credit risk, business trends as well as technical data skills. Automate formulation of business rules in targeting different business objectives. Responsible for the development and execution of new and innovative analytics and as well as being on top of key relevant model updates.

Requirements

PhD in Statistics, Math, Economics, Computer Science or a related quantitative field with at least 3 years of related post-graduate work experience; or Master degree with at least 5 years of related experience
Specific mortgage experience preferred
Minimum of 8+ years of relevant experience applying predictive modeling techniques or data analytics to large datasets is preferred.
5+ years of experience writing statistical or optimization programs to develop models, algorithms and/or to conduct data analytics on large data sets.
Proficiency in programming languages such as SQL (required), Python (required), SAS.
Strong experience with Tableau, PowerPoint and/or Excel
Solid understanding of risk, credit, and the mortgage life cycle.
Strong quantitative, analytical, and problem-solving skills.
Excellent quantitative, analytical, problem-solving, critical thinking and communication skills.
Good presentation skills both verbal and written.
Deep curiosity about new trends and topics in mortgage products and credit risk
Proven ability to analyze risk using quantitative and qualitative information in a time-sensitive environment, outstanding analytical, technical, and problem-solving skills.
Ability to self-teach new technical skills as needed.

Responsibilities

Monitoring credit risk patterns of SF new fundings and proactively identify emerging risk by applying AI/Machine Learning techniques to advance analytics.
Manage the GEO Intelligence Forum which stays on top of emerging macro and mortgage performance patterns across GEOs
Apply sophisticated technical skills to provide deeper insights into credit risk trends using traditional and non-traditional mortgage data.
Enhance analytical ability in the team by building subject matter expertise in risk models, statistical methods, credit policy, credit risk, business trends as well as technical data skills.
Automate formulation of business rules in targeting different business objectives.
Responsible for the development and execution of new and innovative analytics and as well as being on top of key relevant model updates.

Stand Out From the Crowd

Upload your resume and get instant feedback on how well it matches this job.

Upload and Match Resume