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AI Homeowners Association Fee Trend Analyst

Natalie Petrov

Freelance · Job · New_York

About the role

Our mission is to give buyers and lenders a clearer picture of real estate costs before commitment, and one recurring blind spot keeps surfacing in client feedback: HOA fees that jump sharply right after closing. You will build a model that analyzes historical HOA fee trends by property and region, flagging properties where fee increases are statistically likely in the near term based on reserve fund health and past increase patterns. This is a freelance engagement with flexible scope, well suited to someone with quantitative real estate or municipal finance analysis experience who wants project-based work.

Responsibilities

  • Build a model predicting likely near-term HOA fee increases by property and region
  • Incorporate reserve fund health signals where publicly available data exists
  • Validate predictions against historical fee increase records
  • Document methodology in a form client-facing teams can present to buyers
  • Advise on data sourcing improvements as new public records become available

Requirements

  • Prior experience in quantitative real estate or municipal finance analysis
  • Strong Python, SQL, and R skills
  • Comfortable producing client-facing documentation
  • Available for a flexible, project-based engagement

Benefits

  • Fully remote, freelance engagement
  • Flexible scope and schedule
  • Competitive project-based compensation
  • Potential for recurring engagements

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Categories

data science & analytics

Skills

python sql r

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Job Type

Freelance

Level

Senior

Language

English

Salary Range

Negotiable / Competitive

AI Expertise

data science & analytics

Skills

python sql r

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