Staff Analyst, Investor Analytics

About Upstart

Upstart is a leading AI lending marketplace partnering with banks and credit unions to expand access to affordable credit. By leveraging Upstart's AI marketplace, Upstart-powered banks and credit unions can have higher approval rates and lower loss rates across races, ages, and genders, while simultaneously delivering the exceptional digital-first lending experience their customers demand. More than two-thirds of Upstart loans are approved instantly and are fully automated.

Upstart is a digital-first company, which means that most Upstarters live and work anywhere in the United States. However, we also have offices in San Mateo, California; Columbus, Ohio; and Austin, Texas.

Most Upstarters join us because they connect with our mission of enabling access to effortless credit based on true risk. If you are energized by the impact you can make at Upstart, we’d love to hear from you!

The Team

The Investor Analytics team plays the critical role of providing analytical capability across Upstart's organization to enable data-driven decision making. We leverage our analytical and technical skills to support our partners with a multitude of services. This includes understanding our underwriting models, presenting on trends in our loan performance, analyzing market size opportunities, creating financial models, developing our business intelligence pipeline to enable self-service reporting, and architecting/automating of work processes.

As a Staff Data Analyst at Upstart, you will join our Investor Analytics team. You’ll be responsible for driving understanding, insights and decision making relating to our loan credit and financial performance. You’ll partner with our Capital Markets and Lending Partnership teams to help investors, banks, and credit unions to take advantage of our unique technology to achieve their business goals.

Position Location - This role is available in the following locations: Remote

Time Zone Requirements - This team operates on both East and West Coast time zones. 

Travel requirements - As a digital first company, the majority of your work can be accomplished remotely. The majority of our employees can live and work anywhere in the U.S but are encouraged to to still spend high quality time in-person collaborating via regular onsites. The in-person sessions’ cadence varies depending on the team and role; most teams meet once or twice per quarter for 2-4 consecutive days at a time

 

How you’ll make an impact:

• Influence Upstart’s credit platform and investor/lending community through informing decisions, opportunities, and risks, while supported by deep understanding and insights on Upstart’s model, credit, and valuation
• Develop credit monitoring and model performance to conduct in-depth analysis on credit data, trends, and anomalies that drive model and product decisions
• Build foundational financial and performance models, data pipelines, and automated reporting to enable robust and dynamic credit intelligence
• Partner with Capital Markets, Lending Partnership, Data Engineering, Machine Learning, Finance, and other Analytics teams to shape credit metrics and narratives, drive consensus on the state of Upstart platform, and deepen investor/lending partner confidence to invest in our platform
• Mentor junior team members and foster a center of excellence on data, credit, and analytics

 

What we’re looking for: 

• Minimum qualifications:
  • 8+ years work experience in increasingly senior analytical roles in technology and/or financial services industries
  • Experience in credit analytics, business analytics, valuations, and/or financial analytics using Python, R, GSheet (AppScript), Excel (VBA), SAS; 
  • Experience working with large datasets, data modeling, and data pipelines using tools like Databricks, DBT, Looker, Redshift, Snowflake, Tableau; Experience deriving actionable insights from analysis and analytical storytelling
  • Ability to craft executive-ready narratives and presentations around complex business or performance topics and successfully influence C-level decision making
  • Degree in Analytics, Data Science, Economics, Engineering, Mathematics or other quantitative field

• Preferred qualifications:
  • Experience in coaching and mentoring junior team members on technical subjects
  • Experience in credit risk management
  • Demonstrated ability to work collaboratively and in deep partnership with cross-functional teams especially in Finance, Product, Data Engineering, Machine Learning teams