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Causal Inference Jobs in Palatine, IL (NOW HIRING)

Mondo

Lead Decision Science Analyst

Oak Brook, IL · Remote

$80 - $90/hr

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 ...

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Grubhub

Senior Staff Data Scientist

Chicago, IL

Develop causal inference and experimentation frameworks that help Wonder understand which product, operational, and marketplace changes truly drive business impact. * Partner with engineering to ...

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Causal Inference information

See Palatine, IL salary details

$55.3K

$99.7K

$136.2K

How much do causal inference jobs pay per year?

As of Aug 21, 2026, the average yearly pay for causal inference in Palatine, IL is $99,735.00, according to ZipRecruiter salary data. Most workers in this role earn between $86,400.00 and $109,100.00 per year, depending on experience, location, and employer.

What is a causal inference?

A Causal Inference job involves using statistical and computational methods to determine cause-and-effect relationships from data. Professionals in this field work with observational and experimental data to identify causal impacts, often in domains like economics, healthcare, social sciences, and technology. They apply techniques such as propensity score matching, instrumental variables, and difference-in-differences to ensure rigorous analysis. These roles are commonly found in academia, policy research, and data science teams within tech and finance companies. Strong skills in statistics, programming (e.g., Python, R), and experimental design are typically required.

What skills and qualifications are needed for a causal inference position?

Success in a Causal Inference role requires strong statistical knowledge, expertise in experimental and quasi-experimental methodologies, and advanced proficiency in programming languages like R or Python, typically acquired with an advanced degree in statistics, economics, data science, or a related field. Familiarity with specialized statistical software (such as Stata, SAS, or causal inference packages in R/Python), as well as experience with large datasets and machine learning tools, is highly valued. Excellent problem-solving abilities, clear communication, and collaboration skills are essential soft skills for effectively conveying complex findings to diverse teams. These competencies are critical to producing reliable insights that guide evidence-based decision-making in business, healthcare, or policy settings.

What are common challenges faced in a causal inference position?

Professionals in Causal Inference often encounter challenges such as dealing with confounding factors, addressing selection bias, and ensuring the validity of assumptions behind statistical models. They must carefully design experiments or leverage observational data while staying vigilant about potential data quality issues and model limitations. Collaboration with subject matter experts, data engineers, and business stakeholders is common to ensure accurate contextualization of results. Overcoming these challenges requires a mix of technical acumen and strong communication skills to translate complex analyses into actionable recommendations.

What cities near Palatine, IL are hiring for Causal Inference jobs?

Cities near Palatine, IL with the most Causal Inference job openings:

Causal Inference jobs near you
Infographic showing various Causal Inference job openings in Palatine, IL as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% Remote job distribution, with an average salary of $99,735 per year, or $47.9 per hour.

Lead Decision Science Analyst

Mondo

Oak Brook, IL • Remote

$80 - $90/hr

Contractor

Medical, Dental, Vision, Retirement

Posted yesterday

New

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.