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Applied Scientist III

Uber FreightSan Francisco, California

$150,000 - $182,000 / year

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Overview

Schedule
Full-time
Career level
Senior-level
Remote
Hybrid remote
Compensation
$150,000-$182,000/year
Benefits
Health Insurance
Dental Insurance
Vision Insurance

Job Description

Schedule: Full Time Employment
Job Type: Hybrid
Salary Type: Salary
Req #: 2520

About the Role 

As an Applied Scientist III at Uber Freight, you will develop and implement advanced statistical, economic, machine learning, and optimization approaches to solve complex business problems and improve performance. You will apply modeling skills and data-driven methods to enhance our core product experience and top line business metrics. You’ll collaborate closely with Product, Operations, and Engineering teams to turn insights into impact. 

What the Candidate Will Do 

  • Develop creative solutions and build prototypes to business problems using algorithms based on causal inference, statistics, machine learning, and optimization. 
  • Collaborate with engineering and product teams to productionize these solutions and create a lasting impact. 
  • Drive clarity and solve ambiguous, challenging business problems using data-driven approaches, with an emphasis on understanding causal relationships when applicable. 
  • Propose and guide robust frameworks of data analysis to drive business insights and inform decision-making. 
  • Contribute to establishing standard methodologies for data science, including modeling, coding, analytics, and experimentation. 
  • Leverage data to understand product performance and identify improvement opportunities, including analyzing potential causal factors. 
  • Design product experiments and interpret results to draw detailed and impactful conclusions. 
  • Communicate findings and insights to senior management and cross-functional teams. 
  • Provide recommendations to assist quick product ideation and feature launch decisions. 
  • Build intelligent data-driven products to provide the best user experience. 

Basic Qualifications 

  • Bachelor’s degree in Statistics, Machine Learning, Operations Research, Economics, Computer Science, or another related field 
  • 3 years of related experience 
  • Expertise in observational causal inference, econometric, and statistical models  
  • Demonstrated proficiency in programming languages like Python or R for purposes of model development and analysis 
  • Proficiency in SQL for data manipulation and analysis 
  • Proficiency in building and managing data pipelines for purposes of model development or analysis 

Preferred Qualifications 

  • Master’s or Ph.D. in Statistics, Machine Learning, Operations Research, Economics, Computer Science, or a related field 
  • Expertise in time series analysis and forecasting  
  • Experience working on pricing algorithms in a production environment 
  • Proficiency in designing, launching, and analyzing A/B tests or other types of online experiments

Benefits & Compensation for U.S. Employees

Employees working more than 30 hours in the US at Uber Freight are eligible for benefits like a company sponsored health plan, dental and vision benefits, 401k match, financial and mental wellness benefits, parental leave, short- and long-term disability coverage, life insurance and more.  US based employees may also be eligible for a performance or sales incentive bonus program, participation in Uber Freight equity awards, and other types of compensation depending upon the role.

About Uber Freight

Uber Freight helps companies move goods more reliably and efficiently. We bring together the technology, people, and transportation capacity they need, using real‑time data from millions of shipments to guide smarter decisions. That helps customers spot issues early, avoid costly surprises, and deliver on time. Uber Freight works with 1 in 3 Fortune 500 shippers across North America and manages over $17B in freight. Learn more at www.uberfreight.com.

Candidate Privacy Notice

Uber Freight is committed to protecting the privacy of our candidates. We collect and process personal data in accordance with applicable data protection laws. For detailed information on how we handle candidate data, please review our Candidate Privacy Notice.

EEOC

Uber Freight is proud to be an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regards to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.

For California-based roles: The salary range for this role is $150,000.00 - $182,000.00 per year

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FAQs About Applied Scientist III Jobs at Uber Freight

What is the work location for this position at Uber Freight?
This job at Uber Freight is located in San Francisco, California, according to the details provided by the employer. Some roles may also include multiple work locations depending on the requirement.
What pay range can candidates expect for this role at Uber Freight?
Candidates can expect a pay range of $150,000 and $182,000 per year.
What employment applies to this position at Uber Freight?
Uber Freight lists this role as a Full-time position.
What experience level is required for this role at Uber Freight?
Uber Freight is looking for a candidate with "Senior-level" experience level.
What benefits are offered by Uber Freight for this role?
Uber Freight offers following benefits: Health Insurance, Dental Insurance, Vision Insurance, Disability Insurance, Life Insurance, Parental and Family Leave, 401k Matching/Retirement Savings, and Health & Wellness Programs for this position. Actual benefits may vary depending on the employer's policies and employment terms.
What is the process to apply for this position at Uber Freight?
You can apply for this role at Uber Freight either through Sonara's automated application system, which helps you submit applications 10X faster with minimal effort, or by applying manually using the direct link on the job page.