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AI Dynamic Pricing Engine Developer

Miles Andersen

Full-time · Job · Chicago

About the role

Our logistics platform prices 2.8 million freight quotes per day. Each quote needs to balance carrier capacity, route congestion, fuel costs, customer price sensitivity, and competitive positioning — in real time, with a 400ms response budget. The current rule-based pricing model leaves an estimated $18M per year on the table by being too conservative in tight markets and too aggressive in soft ones. You'll build the ML-powered pricing engine that replaces the rule engine. The core challenge is causal inference: we can't run price experiments freely because losing a bid has revenue consequences, so we need to extract causal price-demand signals from observational data. You'll design the causal estimation approach, build the demand model, and integrate it into the existing quote generation pipeline without breaking the latency SLA. The pricing team is four people. You'll collaborate with the economics analyst who understands the market dynamics and the platform engineer who owns the quote API. Expect model decisions to be scrutinized by business stakeholders who think in terms of win rates and margin, not loss functions.

Responsibilities

  • Build ML-powered demand models for freight pricing
  • Design causal inference approaches for extracting price elasticity from observational data
  • Integrate pricing model into the quote generation pipeline within latency constraints
  • Build A/B testing frameworks that balance learning against revenue risk
  • Monitor pricing model performance across market segments and route types
  • Collaborate with economics team to encode domain knowledge into model features

Requirements

  • 3+ years in pricing, revenue management, or applied ML in a business context
  • Experience with causal inference or econometric methods
  • Strong Python skills and proficiency with SQL
  • Familiarity with online learning or bandit algorithms for pricing problems
  • Ability to communicate model decisions to business stakeholders

Benefits

  • Fully remote with flexible hours
  • Health and dental coverage
  • 401(k) with 4% company match
  • $3,000 annual learning budget
  • Quarterly profit-sharing bonus

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Job Type

Full-time

Level

Mid-Level

Language

English

Salary Range

$100k – $130k / year

AI Expertise

AI & Machine Learning Engineers data science & analytics

Skills

python pytorch sql spark statistics aws

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