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

Mondo

Lead Decision Science Analyst

Oak Brook, IL · Remote

$80 - $90/hr

Lead Decision Science Analyst, Remote (EST/ CST hours). Start date is ASAP for this 6-Month ... Design, analyze, and interpret A/B tests and other causal inference approaches, ensuring test ...

Wand

Product 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 ...

Tempus

Data Scientist II, Outcomes Research

Chicago, IL · On-site +1

$100K - $150K/yr

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 ...

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Remote Causal Inference information

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How much do remote causal inference jobs pay per hour?

As of Aug 24, 2026, the average hourly pay for remote causal inference in Mokena, IL is $55.89, according to ZipRecruiter salary data. Most workers in this role earn between $45.87 and $66.20 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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Lead Decision Science Analyst

Mondo

Oak Brook, IL • Remote

$80 - $90/hr

Contractor

Medical, Dental, Vision, Retirement

Posted 4 days ago

Job description

Apply now: Lead Decision Science Analyst, Remote (EST/ CST hours). Start date is ASAP for this 6-Month Contract-to-Hire position. Job Title: Lead Decision Science Analyst Location-Type: Remote (CST/EST Hours required) Start Date: ASAP Duration: 6-Month Contract-to-Hire Compensation Range: $80-90/hr Benefits: Eligible for Health, Dental, Vision, and 401K Visa Sponsorship: Not eligible for visa sponsorship Job Description:
  • This role translates complex data into strategic insights that directly influence product, marketing, and business decisions for the client through causal inference, experimentation, and deep exploratory analytics.
Job Summary
  • Conduct deep exploratory, diagnostic, and causal analyses to identify growth levers and quantify the business impact of key initiatives.
  • Design, analyze, and interpret A/B tests and other causal inference approaches, ensuring test validity and clear stakeholder readouts.
  • Partner cross-functionally with Product, Engineering, Marketing, and Finance leaders to develop and monitor KPIs and evaluate initiative impact.
  • Translate technical findings into clear, actionable recommendations for senior stakeholders through verbal, written, and visual communication.
  • Utilize SQL and Python to extract, manipulate, integrate, and analyze large datasets across multiple data platforms.
  • Identify leading indicators, behavioral trends, and segmentation opportunities to guide organizational strategy.
  • Provide guidance to associate and senior analysts on analytics best practices, experimental design, and statistical rigor.
Minimum Requirements:
  • Bachelor's degree in Business Analytics, Statistics, Mathematics, Econometrics, Engineering, or a related field with significant analytical coursework.
  • 5 years of relevant experience in an analytics role, preferably in product, marketing, or growth analytics.
  • 2 years of experience building dashboards and reports in Power BI, Tableau, or comparable visualization tools.
  • 2 years applying experimentation and causal inference methods (A/B tests, quasi-experiments) in product or marketing contexts.
  • Exceptional SQL skills with a strong track record of working with complex datasets, including data extraction and manipulation.
  • Experience with Azure or other cloud environments
  • Proficiency in Python and/or R for statistical analysis and data manipulation.
  • Strong verbal and written communication skills, with the ability to translate complex concepts into actionable business insights for non-technical stakeholders.
  • Experience with data warehouse and data modeling concepts and procedures.
  • Background in SaaS/technology-focused organization
Preferred Qualifications:
  • MBA or Master's degree in a related analytical field.
  • Experience with Databricks.
  • Experience with IoT, SaaS, or intelligent consumer products and services.
  • Familiarity with Salesforce, SAP, or CDP platforms such as Tealium.
  • Experience with project management and tracking tools such as Jira.