Test design, results synthesis, and the translation of findings into decisions, including the causal inference judgment around when a methodology fits the question and when results generalize. * The ...
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Test design, results synthesis, and the translation of findings into decisions, including the causal inference judgment around when a methodology fits the question and when results generalize. * The ...
New
Test design, results synthesis, and the translation of findings into decisions, including the causal inference judgment around when a methodology fits the question and when results generalize. * The ...
New
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Test design, results synthesis, and the translation of findings into decisions, including the causal inference judgment around when a methodology fits the question and when results generalize. * The ...
New
Test design, results synthesis, and the translation of findings into decisions, including the causal inference judgment around when a methodology fits the question and when results generalize. * The ...
New
Test design, results synthesis, and the translation of findings into decisions, including the causal inference judgment around when a methodology fits the question and when results generalize. * The ...
New
Staff Data Scientist
Westchester, IL · On-site
$100 - $140/hr
Design and analyze experiments (A/B tests, causal inference) to measure model and product impact * Perform feature engineering, data validation, and quality assurance across large, complex datasets
New
Staff Data Scientist
Westchester, IL · On-site
$100 - $140/hr
Design and analyze experiments (A/B tests, causal inference) to measure model and product impact * Perform feature engineering, data validation, and quality assurance across large, complex datasets
New
Statistical Analyst, Education & Employment (Remote Eligible)
Chicago, IL · On-site +1
$70K - $90K/yr
Coursework or experience in some of the following statistical and/or quantitative methods: causal inference at both the design (matching or weighting for comparison group selection) and analysis ...
Statistical Analyst, Education & Employment (Remote Eligible)
Chicago, IL · On-site +1
$70K - $90K/yr
Coursework or experience in some of the following statistical and/or quantitative methods: causal inference at both the design (matching or weighting for comparison group selection) and analysis ...
Director, Epidemiology & Methodological Innovation
Chicago, IL · On-site
$180K - $250K/yr
Lead the development of novel approaches for RWE, including the use of external control arms (ECA), causal inference in high-dimensional data, and the integration of longitudinal clinical data with ...
Director, Epidemiology & Methodological Innovation
Chicago, IL · On-site
$180K - $250K/yr
Lead the development of novel approaches for RWE, including the use of external control arms (ECA), causal inference in high-dimensional data, and the integration of longitudinal clinical data with ...
Director, Epidemiology & Methodological Innovation
$180K - $250K/yr
Lead the development of novel approaches for RWE, including the use of external control arms (ECA), causal inference in high-dimensional data, and the integration of longitudinal clinical data with ...
Director, Epidemiology & Methodological Innovation
$180K - $250K/yr
Lead the development of novel approaches for RWE, including the use of external control arms (ECA), causal inference in high-dimensional data, and the integration of longitudinal clinical data with ...
Director, Epidemiology & Methodological Innovation
Chicago, IL · On-site
$170 - $230/hr
Lead the development of novel approaches for RWE, including the use of external control arms (ECA), causal inference in high-dimensional data, and the integration of longitudinal clinical data with ...
Director, Epidemiology & Methodological Innovation
Chicago, IL · On-site
$170 - $230/hr
Lead the development of novel approaches for RWE, including the use of external control arms (ECA), causal inference in high-dimensional data, and the integration of longitudinal clinical data with ...
... g. causal inference, significance testing, regression analysis, etc. • Demonstrated experience in creating scalable, repeatable processes • Proficiency in reporting / analytics and AI tools ...
... g. causal inference, significance testing, regression analysis, etc. • Demonstrated experience in creating scalable, repeatable processes • Proficiency in reporting / analytics and AI tools ...
Manager, Analytics & Strategy
$120K - $140K/yr
Experience with causal inference and quasi-experimental methods * Experience with machine learning techniques In accordance with the Illinois Pay Transparency Act, we're providing the full salary ...
Manager, Analytics & Strategy
$120K - $140K/yr
Experience with causal inference and quasi-experimental methods * Experience with machine learning techniques In accordance with the Illinois Pay Transparency Act, we're providing the full salary ...
Incrementality Testing/ Causal Inference * AttributionModeling * CustomerAnalytics:Lifetime Value (CLV) Modeling,Segmentation * Generative AI Data Science * Proficiencyinthe following ...
Incrementality Testing/ Causal Inference * AttributionModeling * CustomerAnalytics:Lifetime Value (CLV) Modeling,Segmentation * Generative AI Data Science * Proficiencyinthe following ...
Sr Marketing Data Analyst- Checking & Deposits
$89K - $110K/yr
Marketing Mix Modeling (MMM), attribution, incrementality measurement, or causal inference methodologies. * Customer Lifetime Value (CLV), Net Present Value (NPV), or customer profitability analysis.
Sr Marketing Data Analyst- Checking & Deposits
$89K - $110K/yr
Marketing Mix Modeling (MMM), attribution, incrementality measurement, or causal inference methodologies. * Customer Lifetime Value (CLV), Net Present Value (NPV), or customer profitability analysis.
Data Scientist I supporting social science research, analytics, and AI initiatives
Chicago, IL · On-site
$90K - $100K/yr
... causal inference methods, machine learning, analysis of clustered data, data visualization, use of novel data sources and technologies to improve data gathering, and building AI solutions that ...
Data Scientist I supporting social science research, analytics, and AI initiatives
Chicago, IL · On-site
$90K - $100K/yr
... causal inference methods, machine learning, analysis of clustered data, data visualization, use of novel data sources and technologies to improve data gathering, and building AI solutions that ...
Principal Carelon Research Biostatistician
$136K - $234K/yr
... causal inference, and experimental design preferred. * Experience supporting federally funded research programs, grant-funded studies, or academic research collaborations preferred. * Demonstrated ...
Principal Carelon Research Biostatistician
$136K - $234K/yr
... causal inference, and experimental design preferred. * Experience supporting federally funded research programs, grant-funded studies, or academic research collaborations preferred. * Demonstrated ...
Senior Biostatistician
Chicago, IL · On-site
Causal inference methods * Demonstrated ability to select and apply appropriate statistical methodologies to complex clinical, public health, and observational research questions. Technical Skills
Senior Biostatistician
Chicago, IL · On-site
Causal inference methods * Demonstrated ability to select and apply appropriate statistical methodologies to complex clinical, public health, and observational research questions. Technical Skills
Sr Marketing Data Analyst- Checking & Deposits
Chicago, IL · On-site
$89K - $110K/yr
Marketing Mix Modeling (MMM), attribution, incrementality measurement, or causal inference methodologies. * Customer Lifetime Value (CLV), Net Present Value (NPV), or customer profitability analysis.
Sr Marketing Data Analyst- Checking & Deposits
Chicago, IL · On-site
$89K - $110K/yr
Marketing Mix Modeling (MMM), attribution, incrementality measurement, or causal inference methodologies. * Customer Lifetime Value (CLV), Net Present Value (NPV), or customer profitability analysis.
Data Scientist I supporting social science research, analytics, and AI initiatives
Chicago, IL · Hybrid
... causal inference methods, machine learning, analysis of clustered data, data visualization, use of novel data sources and technologies to improve data gathering, and building AI solutions that ...
Data Scientist I supporting social science research, analytics, and AI initiatives
Chicago, IL · Hybrid
... causal inference methods, machine learning, analysis of clustered data, data visualization, use of novel data sources and technologies to improve data gathering, and building AI solutions that ...
Data Scientist I supporting social science research, analytics, and AI initiatives
Chicago, IL · On-site
... causal inference methods, machine learning, analysis of clustered data, data visualization, use of novel data sources and technologies to improve data gathering, and building AI solutions that ...
Data Scientist I supporting social science research, analytics, and AI initiatives
Chicago, IL · On-site
... causal inference methods, machine learning, analysis of clustered data, data visualization, use of novel data sources and technologies to improve data gathering, and building AI solutions that ...
Principal Carelon Research Biostatistician
$136K - $234K/yr
... causal inference, and experimental design preferred. * Experience supporting federally funded research programs, grant-funded studies, or academic research collaborations preferred. * Demonstrated ...
Principal Carelon Research Biostatistician
$136K - $234K/yr
... causal inference, and experimental design preferred. * Experience supporting federally funded research programs, grant-funded studies, or academic research collaborations preferred. * Demonstrated ...
Design and analyze experiments (A/B tests, causal inference) to measure model and product impact * Perform feature engineering, data validation, and quality assurance across large, complex datasets
Design and analyze experiments (A/B tests, causal inference) to measure model and product impact * Perform feature engineering, data validation, and quality assurance across large, complex datasets
Causal Inference information
Is causal inference still relevant?
Causal inference is a vital skill for data analysts and researchers, as it helps determine cause-and-effect relationships in data. It remains highly relevant across industries such as healthcare, economics, and technology, especially with the increasing availability of large datasets and advanced statistical tools like R and Python. Professionals in this field are in demand for designing experiments, analyzing observational data, and informing decision-making processes.
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 jobs use causal inference?
Causal inference is used in various roles such as data scientist, epidemiologist, econometrician, and policy analyst. These jobs involve analyzing data to determine cause-and-effect relationships, often using statistical tools and programming languages like R or Python. Professionals in these fields work in industries like healthcare, finance, government, and technology to inform decision-making and policy development.
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 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 are the most commonly searched types of Causal Inference jobs in Illinois? The most popular types of Causal Inference jobs in Illinois are:
What are popular job titles related to Causal Inference jobs in Illinois? For Causal Inference jobs in Illinois, the most frequently searched job titles are:
What job categories do people searching Causal Inference jobs in Illinois look for? The top searched job categories for Causal Inference jobs in Illinois are:
What cities in Illinois are hiring for Causal Inference jobs? Cities in Illinois with the most Causal Inference job openings:
Full-time
Medical, Dental, Vision, Retirement, PTO
Posted 3 days ago
New
Grubhub rating
7.2
Based on 13 frontline employees who took The Breakroom Quiz
6th of 24 rated food delivery companies
Job description
About The Opportunity
You'll lead the analytical agenda for customer retention for Grubhub's Growth organization, focused on the levers that drive lifetime value. This includes diagnosing what makes customers loyal, identifying where retention is strongest or weakest across segments and behaviors, and shaping how the organization invests in marketing or experiences to deepen the relationships that matter most. You'll work closely with the analysts embedded in our loyalty and partnerships ecosystem, bringing a cross-program view that connects their work to broader retention strategy.
This is a business analytics role, not a reporting role. You'll diagnose what drives lifetime value, identify opportunities the organization hasn't yet recognized, and translate that work into the narratives that shape where retention investment is directed. Executives will turn to you for a point of view on customer behavior, and that perspective will influence investment decisions.
You will also own the measurement frameworks the Growth organization relies on: customer lifetime value, retention curves, cohort economics, and the goal-setting that connects initiative-level optimization to organization-level KPIs. Reporting in this role is treated as a data product, designed for clarity, adoption, and decision impact rather than as a recurring deliverable.
You'll partner closely with CRM, Portfolio Analytics, Product, and Finance. The problems are ambiguous, the pace is fast, and the work has visibility from team leadership through the executive level. The path forward for the right person is broader strategic scope and increasing executive engagement.
The Impact You Will Make
What You Bring to the Table
Got These? Even Better
As a matter of company policy, Wonder does not sponsor applicants for employment visa status for this role.
Our hybrid model requires 3 days a week in the office. That said, many team members choose to come in more often to take advantage of in-person collaboration and connection. You're welcome-and encouraged-to be in the office up to 5 days a week if it works for you.
#LI-Hybrid
Illinois: $115,000 per year.
New York: $128,000 per year.
Wonder uses geographic-specific salary structures, which means the salary offered may vary depending on where the job is located. The final salary offer will take into account various factors, such as the candidate's skills, education, training, credentials, and experience.
Benefits
The benefits applicable to this role include a competitive compensation package with equity and a 401(k). We also offer a choice of medical, dental, and vision plans, company paid short and long term disability coverage, paid time off including flexible time off for exempt employees, paid vacation for non-exempt employees, and paid sick leave in compliance with applicable law in addition to paid parental leave, discounted meals and exclusive perks across the Wonder family of brands.
Eligibility, effective dates, and available plan options vary by employment classification and location. To learn more about benefits for this role, visit our Careers page here.
A Final Note
At Wonder, we build the best teams by hiring with an objective lens - evaluating people for their potential while championing diversity, equity, and inclusion. We do not discriminate based on race, color, religion, gender identity or expression, sexual orientation, national origin, age, military service eligibility, veteran status, marital status, disability, or any other protected class. As part of our commitment to fair and compliant hiring practices, Wonder participates in the federal government's E-Verify program to confirm employment eligibility. If you need an accommodation during the interview process, please let your recruiter know.
We look forward to hearing from you! We'll contact you via email or text to schedule interviews and share information about your candidacy.
You'll lead the analytical agenda for customer retention for Grubhub's Growth organization, focused on the levers that drive lifetime value. This includes diagnosing what makes customers loyal, identifying where retention is strongest or weakest across segments and behaviors, and shaping how the organization invests in marketing or experiences to deepen the relationships that matter most. You'll work closely with the analysts embedded in our loyalty and partnerships ecosystem, bringing a cross-program view that connects their work to broader retention strategy.
This is a business analytics role, not a reporting role. You'll diagnose what drives lifetime value, identify opportunities the organization hasn't yet recognized, and translate that work into the narratives that shape where retention investment is directed. Executives will turn to you for a point of view on customer behavior, and that perspective will influence investment decisions.
You will also own the measurement frameworks the Growth organization relies on: customer lifetime value, retention curves, cohort economics, and the goal-setting that connects initiative-level optimization to organization-level KPIs. Reporting in this role is treated as a data product, designed for clarity, adoption, and decision impact rather than as a recurring deliverable.
You'll partner closely with CRM, Portfolio Analytics, Product, and Finance. The problems are ambiguous, the pace is fast, and the work has visibility from team leadership through the executive level. The path forward for the right person is broader strategic scope and increasing executive engagement.
The Impact You Will Make
- The retention insight agenda. Diagnosing what drives lifetime value across the customer base, where retention is strengthening or eroding, and what the organization should do about it. Setting analytical priorities proactively rather than responding reactively to requests.
- Customer lifetime value and retention measurement. The frameworks that quantify customer value, how it evolves over time, and how marketing, pricing, product, and care investments compound across the customer lifecycle.
- Cross-program retention strategy. Connecting insight across GH+, partnerships, and the broader customer base to inform where retention investment should be directed. Partnering with program-level analysts to translate their findings into organization-level decisions.
- Experimentation across the lifecycle. Test design, results synthesis, and the translation of findings into decisions, including the causal inference judgment around when a methodology fits the question and when results generalize.
- The reporting layer for retention. Dashboards, analysis-ready datasets, and self-service tools, designed for reusability and adoption, not one-time use. Reinventing what isn't working and automating what shouldn't require manual effort.
- Goal-setting and performance analysis. Partnering with Growth leadership to develop the goals the organization is measured against, then running the analysis that informs whether targets are being met and what to adjust.
- The narrative. Translating analysis into executive-ready stories that move strategy and unlock investment.
What You Bring to the Table
- 4-6+ years in an analytics role with a track record of influencing meaningful business decisions through data
- Demonstrated ability to independently structure ambiguous business questions, conduct sophisticated analysis, and land the resulting narrative with senior stakeholders
- Deep SQL fluency, with the ability to independently extract and analyze complex data to answer high-stakes business questions
- Strong instincts for experimentation and causal measurement, including the judgment to match methodology to the question at hand
- Strong experience with data visualization tools (Tableau, Looker, or similar), with a clear point of view on what makes reporting useful and adopted, and an automation mindset that reduces manual effort over time
- Cross-functional credibility across Marketing, Finance, Product, CRM, and executive stakeholders
- Fluency with adopting AI tools (LLMs, MCPs, and emerging technologies) in your analytical workflow, with a demonstrated portfolio of applied work
- A track record of building reusable analytical infrastructure-systematized datasets, modular reporting layers, or self-service tools-not just delivering one-off analyses
- Up to 10% travel expected
Got These? Even Better
- Experience in subscription, marketplace, or multi-sided platform businesses
- Hands-on experience with loyalty, CRM, or lifecycle marketing analytics
- Experience designing and evolving CLV or retention measurement frameworks
- Experience partnering with cross-functional stakeholders to align on metric definitions and build shared reporting foundations
- Python or similar for advanced analysis and automation
- Consulting background or other exposure to multiple business models
As a matter of company policy, Wonder does not sponsor applicants for employment visa status for this role.
Our hybrid model requires 3 days a week in the office. That said, many team members choose to come in more often to take advantage of in-person collaboration and connection. You're welcome-and encouraged-to be in the office up to 5 days a week if it works for you.
#LI-Hybrid
Illinois: $115,000 per year.
New York: $128,000 per year.
Wonder uses geographic-specific salary structures, which means the salary offered may vary depending on where the job is located. The final salary offer will take into account various factors, such as the candidate's skills, education, training, credentials, and experience.
Benefits
The benefits applicable to this role include a competitive compensation package with equity and a 401(k). We also offer a choice of medical, dental, and vision plans, company paid short and long term disability coverage, paid time off including flexible time off for exempt employees, paid vacation for non-exempt employees, and paid sick leave in compliance with applicable law in addition to paid parental leave, discounted meals and exclusive perks across the Wonder family of brands.
Eligibility, effective dates, and available plan options vary by employment classification and location. To learn more about benefits for this role, visit our Careers page here.
A Final Note
At Wonder, we build the best teams by hiring with an objective lens - evaluating people for their potential while championing diversity, equity, and inclusion. We do not discriminate based on race, color, religion, gender identity or expression, sexual orientation, national origin, age, military service eligibility, veteran status, marital status, disability, or any other protected class. As part of our commitment to fair and compliant hiring practices, Wonder participates in the federal government's E-Verify program to confirm employment eligibility. If you need an accommodation during the interview process, please let your recruiter know.
We look forward to hearing from you! We'll contact you via email or text to schedule interviews and share information about your candidacy.
About Grubhub
Sourced by ZipRecruiter
Grubhub is a leader in the online food delivery industry, primarily functioning in the United States. Headquartered in Chicago, Illinois, it operates in approximately 4,000 U.S. cities. The company provides an online and mobile platform for restaurant pick-up and delivery orders. It was established in 2004 by Matt Maloney and Mike Evans, with the mission of connecting diners with local restaurants. Over the years, Grubhub has been instrumental in streamlining the food order and delivery process. This has enabled it to serve millions of users who can order from their favorite local restaurants through Grubhub's platform. Additionally, Grubhub has increased restaurant reach by providing them with dedicated delivery drivers.
Industry
Internet and it
Company size
1,001 - 5,000 Employees
Headquarters location
Chicago, IL, US
Year founded
2004