Data Scientist - Finance (Hybrid)
Washington, DC, United States
Applications have closed
Fannie Mae
We facilitate equitable and sustainable access to homeownership and quality, affordable rental housing across America.Company Description
At Fannie Mae, futures are made. The inspiring work we do helps make a home a possibility for millions of homeowners and renters. Every day offers compelling opportunities to use tech to tackle housing’s biggest challenges and impact the future of the industry. You’ll be a part of an expert team thriving in an energizing, flexible environment. Here, you will grow your career and help create access to fair, affordable housing finance.
Job Description
As a valued colleague on our team, you will work with your team to apply fundamental techniques to support production of insights, new product or change recommendations, process improvement or automation, and predictive modeling. You will apply basic knowledge of data mining and data analysis methods, have familiarity with common large data processing techniques, computational programing capabilities, and practical problem-solving skills, and articulate solutions to non-technical consumers or partners. Additionally, you will partner with data engineering and data management teams 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 - 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:
- Gather and report on business needs and current capabilities, data availability, and alternative uses from product and/or business owners, data engineers, and platform teams.
- Contribute to implementing recommendations regarding modifications to statistical modeling capabilities.
- Build upon basic predictive analytic capabilities to enhance the delivery of business applications, and support the integration of data and statistical models or algorithms. Apply industry practices in research and testing to product development, deployment, and maintenance.
- Partner with more experienced team members to design modeling applications that support risk measurement, financial valuation, decision making, and business performance.
- Partner with team to design data visualizations, technical documentation, and non-technical presentation materials to communicate ideas and solutions to business partners.
Qualifications
THE EXPERIENCE YOU BRING TO THE TEAM
Minimum Required Experiences
- 0-2 years of relevant experience
- Applying data analytical tools to regression modeling and time series modeling;
- Knowledge of statistical methods, including: developing and testing hypotheses, using experimental design, and running linear and logistic regressions
- Coding, debugging, and using relevant programming languages (SAS, Python, R)
- Strong communication skills both verbal and written
- Ability to present information and/or ideas to an audience in a way that is engaging and easy to understand
Desired Experiences
- Bachelor degree or equivalent
- 2 years of relevant experience
- Experience gathering accurate information to explain concepts and answer critical questions
- Experience defining and managing changes to documents, code, computer programs, websites, and other files to enable collaboration and ensure teams are working from the latest version
- Managing and engaging stakeholders, customers, and vendors, building relationship networks. Working with people with different functional expertise respectfully and cooperatively to work toward a common goal
Tools
Experience using R
Skilled in Python object-oriented programming
Skilled in Microsoft Teams
Skilled in Amazon Web Services (AWS) offerings, development, and networking platforms
Skilled in Excel
Skilled in Tableau
Skilled in SQL
Experience using JIRA
Skilled in SAS
Skilled in RStudio to develop programs in R
Skilled in Plotly
Skilled in TOAD SQL database management tool
Additional Information
Fannie Mae is primarily a hybrid company. We embrace flexibility for our employees while providing office space for in-person work and collaboration. This role is classified as (Remote/Hybrid/Onsite). If you speak with a Recruiter, they will provide you with more information about the definition of this classification.
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.
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Job ID: REF10517M
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.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: AWS Classification Data analysis Data management Data Mining Engineering Excel Finance Jira OOP Plotly Predictive modeling Python R Research SAS SQL Statistical modeling Statistics Tableau Testing
Perks/benefits: Career development Flex hours Health care Home office stipend
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