Applied Scientist III

Uber Freight

Hybrid

Quick summary

Work type
Hybrid
Location
San Francisco
Salary
$150,000–$182,000 / yr
Posted
today

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $170k
This role $166k
$97k most similar roles pay here $233k

This role pays more than 55% of similar roles. Most pay $130,989–$209,000 — the shaded band above. At the midpoint, this role pays about $166k versus about $170k 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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View all roles at Uber Freight

At a glance

TL;DR · Applied Scientist III

As an Applied Scientist III at Uber Freight, you will join a dynamic team to develop and implement advanced statistical, machine learning, and optimization approaches to solve complex business problems. Your day-to-day responsibilities include creating prototypes using causal inference, statistics, and machine learning, collaborating with engineering teams to productionize solutions, and driving clarity on ambiguous challenges through data-driven methods. You will also contribute to establishing standard methodologies for data science and design product experiments to inform decision-making. The role requires expertise in Python or R, SQL, and building data pipelines, along with a background in statistics, machine learning, operations research, economics, or computer science. Experience in time series analysis, pricing algorithms, and A/B testing is preferred.

What you'll do

  • Develop and implement advanced algorithms to solve complex business problems.
  • Build prototypes using causal inference, machine learning, and optimization techniques.
  • Design and manage data pipelines for model development and analysis.
  • Propose and guide robust frameworks for data analysis and decision-making.
  • Conduct product experiments and interpret results to inform business strategies.

What we're looking for

  • Bachelor’s degree in Statistics, Machine Learning, Operations Research, Economics, or Computer Science.
  • 3 years of experience developing and implementing statistical and machine learning models.
  • Expertise in causal inference, econometric, and statistical modeling techniques.
  • Proficiency in Python or R for model development and analysis.
  • Strong skills in SQL for data manipulation and building data pipelines.

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