Staff Data Analyst, Servicing

Upstart · Fintech · Remote · Data Analytics

This role is for a Staff Data Analyst on the Servicing Analytics team at Upstart, an AI lending marketplace. The analyst will partner with Servicing product management, operations, engineering, and ML teams to drive understanding, insights, and data infrastructure for recoveries and collections strategy. Responsibilities include identifying opportunities, designing experiments, conducting quantitative analysis, building BI pipelines, and collaborating with engineering teams to improve data capabilities. The role requires 8+ years of experience in analytical roles in tech and finance, proficiency in SQL, Python/R, experience with large datasets and data pipelines, and a quantitative degree. Experience with A/B testing, consumer lending, and mentoring junior members is preferred.

What you'd actually do

  1. Lead the development of analytical capabilities to support servicing initiatives and drive efficiency improvements.
  2. Create regular executive level presentations to communicate findings and strategic recommendations.
  3. Design experiments and conduct quantitative analysis to test hypotheses about our users and the way they interact with our servicing initiatives, and collaborate with partners to prioritize the right problems and opportunities.
  4. Collaborate with analytics engineering and software engineering to continuously up-level our servicing data capabilities, making new data available as the business expands, and accelerate time to insights.
  5. Develop and maintain business intelligence tools to support reporting and decision-making.

Skills

Required

  • 8+ years work experience in increasingly senior analytical roles in technology and finance industry
  • Strong background in payments, product, or operations analytics
  • hands-on proficient in SQL, Python and/or R
  • Exceptional track record of deriving actionable insights from analysis and analytical storytelling
  • Experience working with large datasets, unstructured data, data modeling, and data pipelines using tools like Databricks, DBT, Looker, Snowflake, Redshift, Tableau, Mode
  • Degree in Economics, Statistics, Mathematics, Engineering, Data Science or other quantitative fields

Nice to have

  • Strong analytical and quantitative background with experience in conducting and evaluating A/B tests, ideally in Financial and/or Operational related fields
  • Expertise in consumer lending, and knowledge of post origination servicing and/or operations
  • Skilled at crafting executive-ready narratives around complex business topics and successfully influence VP+ decision making
  • Demonstrated ability to work collaboratively and in deep partnership with cross-functional teams
  • Demonstrated ability to balance multiple workstreams and priorities; experience influencing up and cross functionally to maximize positive impact to the organization
  • Experience in coaching and mentoring junior team members on technical subjects

What the JD emphasized

  • advanced AI
  • AI lending marketplace
  • AI to reshape access to credit
  • AI-driven decisions
  • Servicing Analytics team
  • Servicing product management, operations, engineering, and ML teams
  • recoveries and collections strategy
  • business intelligence pipelines
  • A/B tests
  • analytics engineering and software engineering
  • servicing data capabilities
  • business intelligence tools