Applied Scientist III - Shipper Pricing

Uber Freight

Hybrid

Quick summary

Work type: Hybrid
Location: San Francisco
Salary: $149,500–$182,350 / yr
Posted: today

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $167k

This role $166k

$122k most similar roles pay here $204k

This role pays more than 52% of similar roles. Most pay $139,000–$195,806 — the shaded band above. At the midpoint, this role pays about $166k 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.

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At a glance

TL;DR · Applied Scientist III - Shipper Pricing

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Join Uber Freight's Shipper Pricing team as an Applied Scientist III, applying machine learning and optimization techniques to enhance real-time bidding algorithms for freight shipping across various auction types. You'll develop creative solutions to balance gross and net revenue, prototype and evaluate these using statistical analysis, and collaborate with engineering teams to deploy them in production. Essential skills include expertise in Python, SQL, Spark, causal inference, and A/B testing methodologies. Ideal candidates have experience in multi-sided marketplaces and translating complex business challenges into technical solutions.

Skills

Python SQL Spark Machine Learning Causal Inference Optimization Algorithms A/B Testing Neural Networks Reinforcement Learning CI/CD

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 solutions.
Establish standard methodologies for data science, including modeling, coding, analytics, and experimentation.
Translate ambiguous business problems into technical solutions for pricing algorithms.

What we're looking for

M.S. or Bachelor's degree in Computer Science, Machine Learning, Operations Research, or equivalent.
3+ years of experience developing and deploying machine learning models and optimization algorithms in production.
Proficiency in Python, SQL, and Spark for data analysis and algorithm development.
Expertise in causal inference, statistical analysis, and A/B testing methodologies.
Experience collaborating with engineering teams to deploy and evaluate machine learning solutions.

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