Applied Scientist III - Shipper Pricing

Uber Freight

Hybrid

Quick summary

Work type
Hybrid
Location
Chicago
Salary
$124,600–$151,950 / yr
Posted
today

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $167k
This role $138k
$116k most similar roles pay here $204k

This role pays less than 76% of similar roles. Most pay $139,000–$195,806 — the shaded band above. At the midpoint, this role pays about $138k versus about $167k for comparable roles.

Based on 240 similar postings.

Employer

About Uber Freight

Uber Freight is a logistics technology platform that connects shippers with carriers to simplify freight transportation, offering digital load booking, pricing transparency, and supply chain management tools.

Uber Freight currently has 11 open roles on FindRole.

Listed pay typically runs $149,750–$182,175 across 8 roles with salary data.

Most-posted roles

View all roles at Uber Freight

At a glance

TL;DR · Applied Scientist III - Shipper Pricing

Join Uber Freight’s Shipper Pricing team as an Applied Scientist III, applying machine learning, causal inference, and optimization techniques to enhance real-time bidding algorithms for freight shipping across various auction types. You’ll develop creative solutions that balance gross and net revenue while collaborating with senior ICs, product managers, engineers, and other scientists daily. Key responsibilities include prototyping and evaluating models through statistical analysis and simulation, deploying these solutions in production, and establishing methodologies for data science practices. Ideal candidates have a strong background in machine learning, optimization algorithms, and experience with Python, SQL, and Spark. Experience in multi-sided marketplaces and reinforcement learning is preferred, as you’ll tackle complex business challenges that impact Uber Freight’s core metrics.

What you'll do

  • Develop algorithms for real-time bidding on shipper freight to balance gross and net revenue.
  • Prototype and evaluate solutions using statistical analysis and simulation techniques.
  • Collaborate with engineering teams to deploy, experimentally evaluate, and productionize pricing solutions.
  • Establish standard methodologies for data science including modeling, coding, analytics, and experimentation.
  • Translate ambiguous business problems into technical solutions for shipper freight algorithms.

What we're looking for

  • M.S. or Bachelor's degree in Computer Science, Machine Learning, Operations Research, or equivalent technical background.
  • 3+ years of experience developing and deploying machine learning models and optimization algorithms in production environments.
  • Expertise in observational causal inference, statistical analysis, and proficiency in Python, SQL, and Spark.
  • Proficiency in designing, launching, and analyzing A/B tests or other types of online experiments.
  • Experience collaborating with engineering teams to deploy and experimentally evaluate solutions.

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