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AI Transit Demand Forecasting Developer

Zaltex Data

Remote · $80k – $100k / year · Contract · Posted 5 months ago

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About the role

Public transit agencies set schedules months in advance based on historical ridership averages. But ridership patterns have changed dramatically — remote work shifted commute peaks, events create unpredictable surges, and new development changes neighborhood demand. Our forecasting system predicts transit demand at the stop level, 2 weeks ahead, so agencies can adjust service frequency before riders experience overcrowding or empty buses. You'll build the demand forecasting models that combine historical ridership data, event calendars, weather forecasts, land use changes, and real-time occupancy sensors. The challenge is the spatial granularity — predictions at the route level are useful, but predictions at the individual stop level (3,000+ stops across a metro area) require handling extreme sparsity and spatial correlation. This is a 9-month contract. You'll work with our transit planning consultant who understands how agencies use demand data to make scheduling decisions and our data engineer who maintains the ridership data pipeline.

Fully remote.

Responsibilities

  • Build stop-level transit demand forecasting models for 2-week horizons
  • Handle extreme sparsity in stop-level ridership data
  • Integrate event calendars, weather, and land use change signals
  • Design spatial correlation models capturing neighborhood interdependencies
  • Validate forecasts against actual ridership and agency scheduling decisions
  • Produce forecast reports formatted for transit planning workflows

Requirements

  • 3+ years in time series forecasting or spatial data science
  • Experience with sparse, spatially correlated data
  • Strong Python and statistical modeling skills
  • Understanding of forecasting evaluation beyond simple MAPE
  • Interest in urban transit and public infrastructure

Benefits

  • Fully remote contract position
  • Competitive monthly rate
  • Work that improves public transit for millions of riders
  • Access to rich transit data
  • Potential for follow-on engagement

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Categories

Data Science & Analytics AI & Machine Learning Engineers

Skills

python pytorch sql statistics gcp

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Job Type

Contract

Level

Mid-Level

Language

English

Salary Range

$80k – $100k / year

AI Expertise

Data Science & Analytics AI & Machine Learning Engineers

Skills

python pytorch sql statistics gcp pandas

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