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Cosign · 2 weeks ago

Data Science Research Intern — Renter Behaviors (UC Graduate & PhD Students)

United States

Internship

Remote

Intern

Cosign is building the modern financial infrastructure for renting, focusing on understanding renter consumer behavior. This research-oriented data science internship is designed for UC graduate students and PhD candidates to apply advanced data science techniques to real-world housing and consumer behavior problems, producing impactful research outputs.

Financial Services

Responsibilities

Analyze large-scale renter and consumer datasets to identify behavioral, demographic, and economic trends

Study how renter behaviors vary across:

California and West Coast regions

Metropolitan areas and submarkets

Economic cycles and housing conditions

Income, credit, and demographic cohorts

Identify leading indicators of renter outcomes and market shifts

Apply statistical modeling, machine learning, and econometric techniques to consumer behavior research

Engineer features that capture behavioral, cohort-level, and market-level signals

Explore predictive and descriptive models to better understand renter decision-making

Produce research papers, white papers, and market reports suitable for external distribution

Collaborate with Cosign leadership to translate technical findings into clear narratives for non-technical audiences

Contribute to Cosign’s broader thought leadership on renter economics and housing access

Qualification

Data ScienceMachine LearningStatisticsEconometricsPythonRAnalytical SkillsInterest in Consumer BehaviorWritten Communication

Required

Currently enrolled UC graduate student or PhD candidate (any UC campus)

Based in California

Graduate-level training in: Data Science, Machine Learning, Statistics, Econometrics, Actuarial Science, Applied Mathematics or a closely related field

Strong analytical and quantitative skills

Experience working with Python, R, or similar analytical tools

Interest in consumer behavior, housing markets, or applied economic research