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Remote Causal Inference Jobs in St Louis, MO (NOW HIRING)

Enterprise Holdings

Data Scientist

Saint Louis, MO · Remote

Team members who choose virtual / remote work should have an adequate space to serve as their home ... Apply causal inference techniques using observational data to uncover relationships * Prepare and ...

Enterprise Holdings

Data Scientist

Saint Louis, MO · On-site +1

Team members who choose virtual / remote work should have an adequate space to serve as their home ... Apply causal inference techniques using observational data to uncover relationships * Prepare and ...

Enterprise Holdings

Data Scientist

Saint Louis, MO · On-site +1

Team members who choose virtual / remote work should have an adequate space to serve as their home ... Apply causal inference techniques using observational data to uncover relationships * Prepare and ...

Bunge

Data Scientist

Chesterfield, MO · On-site +1

... series analysis, causal inference), and machine learning algorithms (e.g., regression ... Experience with geospatial data analysis, remote sensing, satellite imagery processing and deep ...

Bunge North America

Data Scientist

Chesterfield, MO · On-site +1

... series analysis, causal inference), and machine learning algorithms (e.g., regression ... Experience with geospatial data analysis, remote sensing, satellite imagery processing and deep ...

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How much do remote causal inference jobs pay per hour?

As of Aug 26, 2026, the average hourly pay for remote causal inference in St. Louis, MO is $55.24, according to ZipRecruiter salary data. Most workers in this role earn between $45.34 and $65.43 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.

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Data Scientist

Enterprise Holdings

Saint Louis, MO • Remote

Full-time

Re-posted 17 days ago

Enterprise Holdings rating

7.1

Company rating: 7.1 out of 10

Based on 268 frontline employees who took The Breakroom Quiz

117th of 175 rated vehicle equipment hire

Job description

ABOUT THE COMPANY

Enterprise Mobility is a leading provider of mobility solutions, owning and operating the Enterprise Rent-A-Car, National Car Rental and Alamo Rent A Car brands through its integrated global network of independent regional subsidiaries. Enterprise Mobility and its affiliates offer extensive car rental, carsharing, truck rental, fleet management, retail car sales, as well as travel management and other transportation services, to make travel easier and more convenient for customers.   

Privately held by the Taylor family of St. Louis, Enterprise Mobility together with its affiliate Enterprise Fleet Management manages a diverse fleet of 2.4 million vehicles and accounted for nearly $39 billion in revenue through a network of more than 9,500 fully-staffed neighborhood and airport rental locations in more than 90 countries and territories. 

As we continue to build a team that drives us forward, we are excited to announce the opening for a Data Scientist.

ABOUT THE ROLE          

The Data Scientist is a key driver of innovation, transforming data into actionable insights that improve business processes. In this role, you’ll develop cutting-edge analytical products—creating algorithms for automation, building predictive models, designing experiments, and applying causal inference techniques to observational data. You’ll also harness mathematical optimization to identify the most profitable business strategies. Success in this position requires strong collaboration with both technical and non-technical teams to ensure the creation, delivery, and adoption of impactful analytical solutions

This position offers the opportunity to work fully remote within the United States (except for Alaska and/or Hawaii). Team members who choose virtual / remote work should have an adequate space to serve as their home office, and must be able to work a schedule within U.S. Central Standard Time core business hours. This position will require employees to come on site to one of our St. Louis campus locations a few times per year for meetings/events or as needed. #LI-REMOTE

We are committed to a fair and transparent hiring process. Candidates should expect identity verification, video interviews, technical validation of skills, and verification of employment, education, and work authorization. Falsification of information, proxy interviewing, or misrepresentation of experience or location will result in disqualification.


As a Data Scientist focused on revenue management, you will design and deploy advanced deep learning models to forecast demand. These models will enable branch-level decision-making, helping maximize revenue by leveraging historical trends and predictive analytics. In this role, you will collaborate closely with cross-functional teams to develop and implement analytical solutions that drive measurable business impact.

  • Collaborate with the team to design and deliver analytical solutions that drive business impact
  • Extract, clean, and manipulate structured and unstructured data from multiple sources
  • Perform exploratory data analysis to identify patterns, trends, and insights
  • Develop predictive models to support data-driven decision-making
  • Design and oversee experiments, ensuring accurate execution and interpretation of results
  • Apply causal inference techniques using observational data to uncover relationships
  • Prepare and deliver clear documentation of methodologies, findings, and recommendations
  • Create and present insightful reports and presentations for technical and non-technical audiences
  • Partner with cross-functional teams to implement and operationalize analytical solutions

Equal Opportunity Employer/Disability/Veterans


Required:

  • Must be presently authorized to work in the U.S. without a requirement for work authorization sponsorship by our company for this position now or in the future
  • Must reside in the United States (does not include Alaska or Hawaii)
  • Must be able to work a schedule within U.S. Central Standard Time core business hours.
  • Must have a Master’s Degree in a Statistical or Mathematical field (e.g. Engineering, Social Science, or Statistics)
  • Must have two (2+) years of experience with predictive models, statistical inference and deep learning
  • Must have experience using libraries like tensorflow or pytorch
  • Must have experience preparing and giving presentations to technical and non-technical audiences
  • Must have proficiency in R or Python
  • Must be committed to incorporating security into all decisions and daily job responsibilities

Preferred:

  • Doctorate Degree in a Statistical or Mathematical field (e.g. Engineering, Social Science, or Statistics)
  • Experience designing experiments
  • Experience exploring and visualizing data
  • Experience using Linux/Unix
  • Experience using SQL
  • Experience working with data (merging, recording, etc.) from a variety of sources/formats
  • Experience working with observational data to attempt causal inference (e.g. matching, weighting, etc.)

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