The Team and Role

The Data 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, some of which include understanding our underwriting models and 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 Credit Oversight & Analytics horizontal team and lead Credit Analytics efforts. You’ll be responsible for driving understanding, insights and decision making relating to our platform level credit performance and credit infrastructure. You’ll partner with our Data Analytics vertical teams, Machine Learning, and Product teams to help shape the narrative and deepen our expertise in understanding credit performance across Upstart platform.

Position Location - This role is available in the following locations: Remote; San Mateo, CA

Time Zone Requirements - The team operates on the West coast time zones.

Travel Requirements - This team has regular onsite collaboration sessions. These occur 5 days per Month at the San Mateo CA, Columbus OH, or Austin TX office. If you need to travel to make these meetups, Upstart will cover all travel related expenses.

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 and credit

• Lead and develop credit monitoring and model performance analytics to conduct in-depth analyses on credit data, trends, and anomalies that drive model and product decisions

• Build foundational data pipelines and analytical tools to enable robust and dynamic credit intelligence for Upstart analyst community

• Partner with the Data Analytics vertical teams, Machine Learning, Product, and Engineering teams to shape credit metrics and narratives, driving consensus in the state of Upstart platform

• Mentor junior team members on best practices and foster a center of excellence on data, credit, and analytics

Minimum qualifications:

• 5+ years work experience in increasingly senior analytical roles in technology and finance industry

• Experience in credit analytics, valuation, and/or financial analytics development with python, R, GSheet (AppScript), Excel (VBA), SAS

• Experience working with large datasets, data modeling, and data pipelines using tools like Databricks, DBT, Looker, Snowflake, Redshift

• Degree in Economics, Mathematics, Engineering, Data Science or other quantitative fields

Preferred qualifications:

• Experience in coaching and mentoring junior team members on technical subject

• Ability to craft executive-ready narratives around complex business or performance topics, leveraging visualization and dashboards (e.g., Tableau, PowerBI, Looker), and to successfully influence and drive C-level decision-making

• Demonstrated ability to work collaboratively and in deep partnership with cross-functional colleagues especially in Finance, Product, Data Engineering, ML teams

• Experience in consumer lending, and/or knowledge of the consumer finance market, capital markets

What you'll love: 

• Competitive Compensation (base + bonus & equity)

• Comprehensive medical, dental, and vision coverage with Health Savings Account contributions from Upstart 

• 401(k) with 100% company match up to $4,500 and immediate vesting and after-tax savings

• Employee Stock Purchase Plan (ESPP)

• Life and disability insurance

• Generous holiday, vacation, sick and safety leave  

• Supportive parental, family care, and military leave programs

• Annual wellness, technology & ergonomic reimbursement programs

• Social activities including team events and onsites, all-company updates, employee resource groups (ERGs), and other interest groups such as book clubs, fitness, investing, and volunteering

• Catered lunches + snacks & drinks when working in offices

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