Quantitative Risk Analysis Associate II

Freddie Mac; McLean (VA); On-site; USD 84,000 - 126,000; Full time

Job summary

Freddie Mac is seeking a Quantitative Risk Analysis, Associate II to join the Credit Analytics & Reporting team in the Single-Family division in McLean, VA. The role involves developing data understanding, designing analytical approaches, and preparing reports and presentations to support risk decisions.

Responsibilties include monthly baseline reporting, ensuring proper controls, performing ad-hoc analytics, and collaborating across the organization to meet business objectives.

Qualifications

• Bachelor's degree in a quantitative field plus 1–3 years of relevant experience in mortgage or financial services.
• Proficiency in SAS and SQL for data analysis and reporting.
• Experience with large dataset manipulation; familiarity with R, Python, and Tableau is preferred.

Responsibilities

• Implement baseline processes and reports monthly and interpret results related to credit risk management.
• Maintain controls and documentation for processes and reports.
• Perform ad-hoc analytics to support credit policy decisions.
• Cleanse, manipulate and analyze large datasets using statistical software.
• Collaborate across teams to meet business objectives.

Skills

SAS programming

SQL programming

Analytical skills

Communication skills

Education

Bachelor's Degree in Statistics, Economics, Finance, Mathematics, Computer Science, Data Science or related field

Tools

R

Python

Tableau

Job description

Opened Recently Location McLean, VA Category Quantitative Analytics & Data Job Id JR17622

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:

We are seeking a Quantitative Risk Analysis, Associate II to join the Credit Analytics & Reporting team in the Single-Family division. This position will be tasked with developing deep understanding of data and current code, designing analytical approaches for business questions and scenario evaluations, managing data research, analyses and preparation of reports and presentations.

Our Impact:

• Our team is responsible for producing reporting packages to monitor trends and performance.
• We analyze different test and learn or pilot programs to assess risk of the
• offerings and create reports to monitor these offerings closely to assess broad roll out.
• We perform significant user activities for different enterprise models for user acceptance testing and provide feedback.

Your Impact:

• Implement baseline processes and reports monthly and interpret results as it relates to credit risk management.
• Follow appropriate controls and standards established to maintain and build documentation for processes & reports.
• Participate in performing ad-hoc analytics in support of credit policy.
• Cleanse, manipulate and analyze large datasets using statistical software.
• Collaborate with team members and interact across organizational lines to meet business objectives.

Qualifications:

• Bachelor's Degree in Statistics, Economics, Finance, Mathematics, Computer Science, Data Science or related field, advanced Degree is a plus
• Minimum 1-3 years of relevant experience, preferably in mortgage industry or financial services
• Demonstrated proficiency in programming languages, preferably SAS and SQL
• Experience in analyzing and manipulating large datasets
• Prefer recent professional experience with analytical and/or data manipulation tools such as R and Python and Tableau for data visualization
• Knowledge of and experience with single-family mortgage credit risk data, preferably related to GSEs

Keys to Success in this Role:

• Self-motivated, pro-active, and results-driven problem solver.
• Proven quantitative, analytical and problem-solving skills.
• Strong communication skills both oral and written.
• Excellent SAS and SQL programming skills.
• Manage multiple priorities, meet deadlines, identify and raise issues appropriately to management.

We consider all applicants for all positions without regard to gender, race, color, religion, national origin, age, marital status, veteran status, sexual orientation, gender identity/expression, physical and mental disability, pregnancy, ethnicity, genetic information or any other protected categories under applicable federal, state or local laws. We will ensure that individuals are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

A safe and secure environment is critical to Freddie Mac's business. This includes employee commitment to our acceptable use policy, applying a vigilance-first approach to work, supporting regulatory mandates, and using best practices to protect Freddie Mac from potential threats and risk. Employees exercise this responsibility by executing against policies and procedures and adhering to privacy & security obligations as required via training programs.

CA Applicants: Qualified applications with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.

Time-type:Full timeFLSA Status:Non-Exempt

Freddie Mac offers a comprehensive total rewards package to include competitive compensation and market-leading benefit programs. Information on these benefit programs is available on our Careers site.

This position has an annualized market-based salary range of $84,000 - $126,000 and is eligible to participate in the annual incentive program. The final salary offered will generally fall within this range and is dependent on various factors including but not limited to the responsibilities of the position, experience, skill set, internal pay equity and other relevant qualifications of the applicant.