Senior Data Analyst - CreditFull-time
MPOWER is a fast-growing startup, based in Washington D.C. and focused on removing financial barriers to higher-education. MPOWER enables students from around the world to financially access higher-education at top U.S. universities. Our global team is composed of ex-management consultants, financial services and technology professionals, and other experts in their respective fields. As a FinTech startup backed by a global Private Equity firm, we move extremely fast and leverage the latest technologies, global best practices, and heavy-analytics to tackle one of the biggest challenges in financial inclusion. We work hard, have fun, and believe greatly in our cause. For us, this mission is personal.
As a member of our team, you’ll be challenged to think creatively in an environment where ideation and implementation happen very quickly. We review all our staff members for promotion every 6 months and provide the resources they need to further their skills and grow with the company. MPOWER is committed to cultivating your strengths and curiosity and helping you make an immediate impact.
This is a full-time position, based in our Washington, D.C. office.
You will be directly responsible for analyzing proprietary and public databases, creating robust quantitative models and presenting insights to the executive team. This includes, but is not limited to:
- Develop scalable, innovative approaches to extracting, managing and analyzing existing data.
- Identify appropriate analytical tools and methods and use them to analyze large data sets of public, private, and proprietary data .
- Perform analysis to support loan product design, pricing, market sizing, and channel strategies.
- Develop robust quantitative models to support the credit analytics team.
- Interpret the results and use insights to drive product enhancements and new product development.
- Maintain a high level of awareness of, and be an advocate for, current and emerging data, technology and industry strategies and trends.
- Undergraduate degree in a quantitative / scientific field (e.g., econometrics, financial mathematics, data science, systems and information engineering, etc…); advanced degree preferred.
- 1-4 years experience in the data practices field and hands-on experience in model development, statistical methodologies and/or quantitative analysis.
- Experience in banking, financial services or related field preferred.
- Experience with statistical software such as R or Python, SAS, or SPSS and SQL, relational database design and methods for efficiently retrieving data from databases.
- Advanced data modeling skills and experience setting up and manipulating large data tables.
- Experience with integrating large-scale heterogeneous datasets.
- Experience in alternative / thin file credit risk scoring, a plus.
- Knowledge of business intelligence and data warehousing.
- Extremely detail oriented and organized.
In addition, the candidate will be comfortable working in a start-up environment, meaning a small agile team, fast-evolving roles and responsibilities, variable workload and tight deadlines, a high degree of autonomy, and 80-20 everything.
Send us your resume with a short statement of interest to email@example.com.