2

Remote Causal Inference Jobs in Chicago, IL (NOW HIRING)

Product Data Analyst

Chicago, IL · Remote

$145K - $175K/yr

Causal inference methods (diff-in-diff, regression discontinuity, propensity matching) * Prior work ... Experience building metrics frameworks or KPI hierarchies from scratch How we work Fully remote ...

Stay current with the latest methodological advances in RWE, including causal inference and ... Additionally, for remote roles open to individuals in unincorporated Los Angeles - including remote ...

Remote Causal Inference information

See Chicago, IL salary details

$17

$58

$83

How much do remote causal inference jobs pay per hour?

As of Aug 4, 2026, the average hourly pay for remote causal inference in Chicago, IL is $58.53, according to ZipRecruiter salary data. Most workers in this role earn between $48.03 and $69.33 per hour, depending on experience, location, and employer.

What is a remote causal inference?

A Remote Causal Inference job involves using statistical and analytical methods to determine cause-and-effect relationships from data, often for fields like healthcare, social sciences, or business. Professionals in this role work remotely, leveraging tools such as R, Python, or specialized software to analyze experiments, observational studies, or large datasets. Their insights help organizations make data-driven decisions, design better interventions, and accurately measure the impact of policies or treatments. Strong skills in statistics, machine learning, and communication are essential for success in this position.

What are the key skills and qualifications needed to thrive as a remote causal inference specialist?

To thrive as a Remote Causal Inference Specialist, you need strong quantitative and statistical skills, a solid background in econometrics or data science, and typically an advanced degree in a related field. Proficiency with statistical programming languages such as R or Python, experience with causal inference frameworks like propensity score matching or instrumental variables, and familiarity with data visualization tools are crucial. Outstanding problem-solving abilities, clear communication, and self-motivation are essential soft skills for working independently and conveying complex results to non-technical stakeholders. These skills enable accurate, actionable insights from data, which drive evidence-based decision-making in remote, collaborative environments.

How does a remote causal inference specialist typically collaborate with cross-functional teams, and what tools are commonly used?

As a remote Causal Inference specialist, you’ll frequently work with data scientists, product managers, and engineers to design and interpret experiments, analyze observational data, and provide actionable insights. Collaboration usually happens through regular video meetings, shared documentation, and project management tools. Commonly used platforms include Slack or Microsoft Teams for communication, GitHub for code collaboration, and Jupyter Notebooks or RMarkdown for sharing reproducible analyses. These tools help ensure transparency and maintain strong teamwork despite the remote environment.
What are the most commonly searched types of Causal Inference jobs in Chicago, IL? The most popular types of Causal Inference jobs in Chicago, IL are:
What are popular job titles related to Remote Causal Inference jobs in Chicago, IL? For Remote Causal Inference jobs in Chicago, IL, the most frequently searched job titles are:
What job categories do people searching Remote Causal Inference jobs in Chicago, IL look for? The top searched job categories for Remote Causal Inference jobs in Chicago, IL are:
What cities near Chicago, IL are hiring for Remote Causal Inference jobs? Cities near Chicago, IL with the most Remote Causal Inference job openings:

Staff Machine Learning Engineer

Uber Technologies, Inc.

Chicago, IL • On-site, Remote

Full-time

Retirement

Posted 4 days ago


Uber rating

6.9

Company rating: 6.9 out of 10

Based on 112 frontline employees who took The Breakroom Quiz

4th of 9 rated taxi private hire


Job description

About the Role

Uber Freight Marketplace is building the next generation of logistics technology by leveraging Uber's proven marketplace playbook to freight. As part of a small, high-impact team, you'll help bring expertise from Uber's mobility and delivery marketplaces into a rapidly evolving industry, developing pricing, matching, recommendation, and optimization systems that will disrupt the freight industry ($1T TAM). Uber Freight is at a very early stage, with just 0.4% of the pie now, and it's a rare opportunity to solve challenging marketplace problems with AI/ML and marketplace optimization while shaping how the freight industry transforms.

We are looking for a highly motivated Machine Learning Engineer to join Uber's Marketplace team to modernize the Uber Freight marketplace team. It is a fascinating area with challenges in predictive modeling, causal inference, constrained optimization, reinforcement learning, marketplace design, etc. The business is about to elevate and this role has a huge growing opportunity.

What You'll Do

This role requires end to end ownership for the ML models in UF marketplace (cost prediction, booking probability, demand elasticity, etc.). While your job is mostly about model development, you will work with backend engineers together to put them in production and make sure they work as expected.

Basic Qualifications
 

  • 6+ years of experience developing ML models to solve business problem.
  • Bachelor's degree in Computer Science, Computer Engineering, or related fields.
  • Familiar with modern AI/ML frameworks (e.g., PyTorch).

 Preferred Qualifications

  • Product experience will be a big plus for this role. Adaptive development of ML models to the business context is critical. 
  • Previous experience with state-of-the-art marketplace technology is preferred.
  • Experience with causal inference and constrained optimization

Ready to Ride?


This isn't the kind of place where you follow a playbook - it's where you help write one. If you're driven by impact, energized by challenge, and ready to shape how the world moves - we'd love to hear from you.


You may be eligible for bonuses, equity, and other compensation, as well as a range of benefits. Explore our benefits.


Offices remain key to collaboration and Uber's culture. Unless approved for full remote work, employees must spend at least 50% of their time in-office. Some roles, like those at greenlight hubs, require full-time in-office presence. Ask your Recruiter for details about this role's requirements.


Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard 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. If you have a disability or special need that requires accommodation, please let us know by completing this form.

For Chicago, IL-based roles: The base salary range for this role is USD $209,000 per year - USD $232,000 per year.


For New York City, NY-based roles: The base salary range for this role is USD $232,000 per year - USD $258,000 per year.


For San Francisco, CA-based roles: The base salary range for this role is USD $232,000 per year - USD $258,000 per year.


For Seattle, WA-based roles: The base salary range for this role is USD $232,000 per year - USD $258,000 per year.


For Sunnyvale, CA-based roles: The base salary range for this role is USD $232,000 per year - USD $258,000 per year.


For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits.


What Uber employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom