Senior Applied Scientist, Shipper Pricing

Uber Freight

Confirmed live yesterday High trust
Hybrid

Quick summary

Work type
Hybrid
Location
Chicago, IL
Salary
$152,500–$186,000 / yr
Posted
147 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $192k
This role $169k
$136k most similar roles pay here $235k

This role pays less than 66% of similar roles. Most pay $159,000–$224,743 — the shaded band above. At the midpoint, this role pays about $169k versus about $192k 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 3 open roles on FindRole.

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At a glance

TL;DR · Senior Applied Scientist, Shipper Pricing

As a Senior Applied Scientist on the Shipper Pricing team, you will apply machine learning, causal inference, and optimization techniques to develop and improve algorithms for real-time bidding on shipper freight. You will build creative algorithms to balance gross and net revenue across various auction types, including open, sealed, and reverse waterfall auctions. Your daily work involves prototyping solutions using statistical analysis and simulation, collaborating with engineering teams to productionize models, and leveraging data to identify performance improvements through causal factor analysis. The role requires expertise in Python, SQL, and Spark, with preferred experience in neural networks, reinforcement learning, and pricing algorithms for multi-sided real-time marketplaces. You will solve complex problems regarding strategic agent behavior in freight markets while establishing standard methodologies for modeling, coding, analytics, and experimentation to influence technical direction and product feature decisions.

What does a Applied Scientist earn?

Median $208800 from 47 postings across 10 companies.

See salary data

What you'll do

  • Develop algorithms to optimize gross and net revenue trade-offs for real-time bidding on shipper freight.
  • Prototype and evaluate technical solutions using statistical analysis and simulation techniques.
  • Partner with engineering teams to deploy and productionize machine learning models and optimization algorithms.
  • Analyze product performance data to identify improvement opportunities and determine causal factors.
  • Establish standard methodologies for modeling, coding, analytics, and experimentation across the data science team.
  • Communicate technical findings and insights to senior management and cross-functional partners.
  • Provide recommendations to guide product ideation and feature launch decisions.

What we're looking for

  • Ph.D. or M.S. in Computer Science, Machine Learning, or Operations Research, or an equivalent technical background.
  • 4+ years of experience developing and deploying machine learning models and optimization algorithms in production environments.
  • Experience designing, executing, and analyzing experiments to measure the impact of changes to production ML models.
  • Expertise in observational causal inference or statistical analysis.
  • Proficiency in Python, SQL, and Spark.
  • Experience developing neural network (NN) algorithms.
  • Experience developing and deploying pricing algorithms for multi-sided real-time marketplaces with strategic agent behavior.
  • Experience in reinforcement learning and causal machine learning.

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