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Junior AI Neighborhood Amenity Scoring Developer

Valtrix Solutions

Remote · $60k – $80k / year · Full-time · Posted 4 months ago

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About the role

A property valuation that doesn't account for neighborhood amenities is incomplete. The same 3-bedroom house commands a 22% price premium if it's walkable to a grocery store, a park, and a coffee shop versus a comparable house that requires a car for all three. Amenity scoring — quantifying the value of proximity to services, green space, transit, schools, and retail — is a meaningful component of automated valuation that most models treat too simply. We power automated valuation models for 40 mortgage lenders, REITs, and iBuyers. Amenity scoring is a module in the valuation stack, and it's due for a rebuild. The current implementation uses simple proximity counts. We want a model that weights amenity types by actual observed price impact, handles temporal changes (a coffee shop opening in 2022 affects values differently than one that's been there for 10 years), and captures synergy effects between amenity combinations. As a junior developer, you'll build and maintain the amenity data pipeline — pulling from places APIs, aggregating temporal presence data, computing proximity features, and delivering amenity scores to the valuation model. Senior engineers define the feature weighting methodology; your job is to make the data reliable, complete, and fresh.

Fully remote.

Responsibilities

  • Build amenity data pipeline pulling from places APIs across 40 markets
  • Implement temporal amenity tracking recording opening dates and closures for amenity scoring
  • Compute proximity and accessibility features for each property in the valuation database
  • Create amenity category classification ensuring consistent taxonomy across data sources
  • Monitor pipeline data quality and flag markets with incomplete coverage
  • Deliver scored amenity features to the valuation model ingestion pipeline on schedule

Requirements

  • 1+ year of Python and SQL development experience
  • Basic familiarity with geospatial data and APIs
  • Interest in real estate, proptech, or geospatial analytics
  • Attention to detail in data completeness and temporal accuracy
  • Reliable async communication and documentation habits

Benefits

  • Fully remote with flexible schedule
  • Health and dental insurance
  • $1,500 annual learning budget
  • Mentorship from senior property data engineers
  • 401(k) with match

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Categories

Data Science & Analytics AI Business, Marketing & Strategy

Skills

python sql pandas statistics fastapi

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Job Type

Full-time

Level

Junior

Language

English

Salary Range

$60k – $80k / year

AI Expertise

Data Science & Analytics AI Business, Marketing & Strategy

Skills

python sql pandas statistics fastapi gcp

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