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  • Finance - Data Science - Senior Associate

    Fannie Mae (Washington, DC)



    Apply Now

    At Fannie Mae, the inspiring work we do helps make a home a possibility for millions of homeowners and renters. Every day offers compelling opportunities to impact the future of the housing industry while being part of a collaborative team thriving in an energizing environment. Here, you will grow your career and help create access toaffordable housing finance.

    Job Description

    As a valued colleague on our team, you will use moderately complex techniques to produce insights, new product or change recommendations, process improvement or automation, and predictive modeling to support efforts to estimate credit risk for multifamily loans. You will use data mining and data analysis methods, be adept with common large data processing techniques, computational programing capabilities, practical problem-solving skills, and have an ability to articulate solutions to non-technical consumers or partners. As a senior associate, you will partner with credit modeling teams and multifamily risk management team to apply data mining techniques to external or created data sources in preparation for analysis or use of enterprise data assets.

     

    *THE IMPACT YOU WILL MAKE*

    The* Finance - Data Science - Senior Associate* 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:

    * Use advanced mathematical, analytical, or econometric tools to create algorithms and analyses that will be used to support the Multifamily CECL and DFAST/forecasting processes within the Finance organization.

    * R esearch and evaluate model results and perform credit-related analyses for both expected and stress scenarios including CECL/DFAST.

    * Collaborate with product and/or business owners, data engineers, and platform teams to understand business needs and current capabilities, data availability, and alternative uses.

    * Implement new statistical modeling capabilities.

    * Apply analytic capabilities and build upon advanced analytic capabilities to enhance the delivery of business applications, and support the integration of data and statistical models or algorithms.

    * Design new modeling applications to support risk measurement, financial valuation, decision making, and business performance.

    * Design data visualizations, technical documentation, and non-technical presentation materials to communicate complex ideas and solutions to business partners.

    *THE EXPERIENCE YOU BRING TO THE TEAM*

    *Minimum Required Experiences:*

    * 2 years

    * Bachelors degree in Business Analytics, Computer Science, Data Science, Engineering Finance, Math, Physics, Statistics, or a related field

    *Desired Experiences*

    * Masters or PhD* in Data Science, Economics, Math, Statistics, or a related field (*or comparable experience)

    * Prior quantitative and finance training, including forecasting/stress testing (DFAST) and or CECL knowledge.

    * Strong analytical and problem-solving skills to conduct analysis to address complexbusiness problems

    * Programming including coding, debugging, and using relevant languages such asPython, R, SQL,or similar

    * Experien

    * ce in the process of analyzing data to identify trends or relationships to generatebusiness insights andinform conclusions about the data

    * Expertise in visualizing data to identify, summarize and explain observed data patterns

     

    Finance - Data Science - Senior Associate

     

    Target Pay Range: $121,000 - $158,000 a year

     

    \#LI-Hybrid #LI-ME1

    Qualifications

    Education:

    Bachelor's Level Degree (Required), Master's Level Degree

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

     

    For most roles, employees are expected to work onsite on a regular basis at their designated office location. In-office work cadence is determined by your manager. Proximity within a reasonable commute to your designated office location is preferred unless the job is noted as open to remote.

     

    Fannie Mae is an equal opportunity employer and considers qualified applicants for employment without regard to race, color, religion, sex, national origin, disability, age, sexual orientation, gender identity/gender expression, marital or parental status, or any other protected factor. Fannie Mae is committed to providing reasonable accommodations to qualified individuals with disabilities who are employees or applicants for employment, unless to do so would cause undue hardship to the company. If you need assistance using our online system and/or you need a reasonable accommodation related to the hiring/application process, please complete this form .

     

    The hiring range for this role is set forth below. 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 .

    Requisition compensation:

    121000

     

    to

     

    158000

     

    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 [email protected].

     


    Apply Now



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