Staff Data Analyst, Servicing

About the role

You will own the analytical strategy that defines how Upstart's Servicing business measures success and drives operational excellence. This role requires you to translate ambiguous business problems into clear analytical roadmaps and own the end-to-end execution of complex data initiatives. You will act as a key thought partner to Servicing product management and operations, shaping the direction of recoveries and collections strategy through data-led insights. A core part of this role is building and mentoring, where you will elevate the analytical capabilities of junior team members and foster a culture of rigorous, curiosity-driven analysis. You will leverage advanced experimentation and predictive modeling to uncover hidden opportunities and ensure our data infrastructure scales with business ambition. Your work will directly influence how millions of customers experience credit recovery and collections, ensuring decisions are both impactful and human-centered. You will be expected to communicate complex findings simply and persuasively to executives and technical partners alike.

Key facts

What you'll do

Lead the design and implementation of analytical frameworks that measure the end-to-end performance of Servicing initiatives.

Create compelling executive-level narratives and dashboards that translate complex data into strategic recommendations for senior leadership.

Design and analyze A/B tests and quasi-experimental studies to evaluate the impact of new servicing strategies on user behavior and financial outcomes.

Partner with analytics engineering and software engineering teams to modernize data pipelines, ensuring new datasets are timely, reliable, and scalable.

Develop and maintain business intelligence tools in Looker and Tableau to support real-time decision-making and operational monitoring.

Conduct in-depth analyses of large and unstructured datasets using SQL, Python, and R to identify root causes and opportunity areas.

Collaborate with product and operations stakeholders to prioritize high-impact problems and align analytical work with business objectives.

Build and maintain data models in Snowflake and Redshift that enable fast, accurate, and consistent reporting across the servicing lifecycle.

Mentor junior analysts and data practitioners, elevating the standard of analytical rigor, documentation, and insight generation across the team.

Champion the adoption of best practices in data governance, ensuring that new data sources are integrated in a secure and compliant manner.

Drive the development of forecasting and optimization models that improve the efficiency and effectiveness of collections and recoveries.

Establish clear documentation standards for analytical assets, ensuring transparency and reproducibility for all team members.

Act as the central analytical partner for cross-functional projects, ensuring alignment between data, product, and business stakeholders.

Continuously explore emerging tools and methodologies to keep the team at the forefront of analytics and experimentation in credit servicing.

Requirements

8+ years of progressively responsible work experience in analytics, technology, finance, or a related quantitative field.

Demonstrated proficiency in SQL, Python, and/or R for data manipulation, analysis, and visualization.

Strong background in payments, product, or operations analytics with a history of delivering actionable insights.

Exceptional analytical and communication skills, with the ability to distill complex findings into clear, executive-level recommendations.

Experience working with large datasets, unstructured data, data modeling, and data pipelines using tools such as Databricks, DBT, Looker, Snowflake, Redshift, Tableau, and Mode.

Bachelor's degree or higher in Economics, Statistics, Mathematics, Engineering, Data Science, or another quantitative field that provides a solid grounding in analytical and problem-solving skills.

Proven ability to manage multiple priorities in a fast-paced, deadline-driven environment while maintaining a high standard of accuracy.

Commitment to maintaining data integrity, security, and compliance in all analytical practices and deliverables.

Nice to have

Strong analytical and quantitative background with experience in conducting and evaluating rigorous experiments in a product environment.

Experience building and maintaining data products that enable cross-functional decision-making and operational efficiency.

Background in lending, credit, or financial services with an understanding of risk, compliance, and regulatory considerations.

Experience mentoring and influencing peers in a matrixed organization to drive data-informed change.

Practical notes

Employment is contingent upon successful completion of background checks.

All hires must comply with Upstart's policies and procedures, which may include monitoring and recording communications related to company business on Upstart systems.

Upstart is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status.

You must be authorized to work in the United States. No current sponsorship available.

The majority of this role is remote, with flexibility to work from home; however, occasional in-person collaboration may be required for team onsites and planning sessions.

This role may be filled at multiple levels with different compensation bands based on location and relevant experience.