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Phd Causal Inference Jobs in Deerfield, IL (NOW HIRING)

Everpure

Principal Economist, GTM Science

Chicago, IL · On-site

Deep grounding in causal inference methodologies, including causal forests, treatment-effect ... Preferred : • PhD in Economics, Econometrics, or an equivalent quantitative discipline, such as ...

Grubhub

Senior Staff Data Scientist

Chicago, IL

Develop causal inference and experimentation frameworks that help Wonder understand which product ... What You Bring to the Table * 8+ years of industry experience with MS or 6+ years with PhD in ...

Everpure

Principal Economist, GTM Science

Chicago, IL · On-site

PhD in Economics, Econometrics, or an equivalent quantitative discipline, such as Applied Economics or Quantitative Marketing, preferred. * Advanced Econometric & Causal Inference Expertise: Deep ...

Everpure

Principal Economist, GTM Science

Chicago, IL · On-site

$168K - $269K/yr

PhD in Economics, Econometrics, or an equivalent quantitative discipline, such as Applied Economics or Quantitative Marketing, preferred. * Advanced Econometric & Causal Inference Expertise: Deep ...

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Phd Causal Inference information

See Deerfield, IL salary details

$40.7K

$125K

$181.5K

How much do phd causal inference jobs pay per year?

As of Aug 15, 2026, the average yearly pay for phd causal inference in Deerfield, IL is $125,010.00, according to ZipRecruiter salary data. Most workers in this role earn between $106,800.00 and $140,300.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a PhD causal inference researcher?

To thrive as a PhD Causal Inference researcher, you need advanced knowledge of statistics, econometrics, and causal modeling, typically supported by a doctoral degree in a quantitative field. Familiarity with statistical programming languages (such as R or Python), specialized software (like STATA or SAS), and experience with experimental or quasi-experimental methods are essential. Strong analytical thinking, attention to detail, and the ability to communicate complex findings clearly make a candidate stand out. These skills ensure rigorous, credible research that can inform policy, product development, or scientific understanding by accurately identifying causal relationships.

What collaborative opportunities can a PhD specializing in causal inference expect within a multidisciplinary research team?

PhD professionals in Causal Inference frequently collaborate with experts from fields such as epidemiology, economics, computer science, and public health. They often work closely with data scientists, subject matter experts, and statisticians to design studies, interpret complex datasets, and develop robust analytical models. This multidisciplinary environment fosters continuous learning and often leads to co-authorship on research publications, participation in grant writing, and involvement in high-impact policy or product decisions. Effective communication and teamwork skills are essential to translate technical findings for diverse audiences and drive actionable insights.

What is a PhD in causal inference?

A PhD in Causal Inference is an advanced research degree focused on understanding and identifying cause-and-effect relationships using statistical and computational methods. Students in this field learn to design studies, analyze data, and develop new methodologies to answer complex causal questions in areas such as social sciences, medicine, economics, and artificial intelligence. Graduates often work in academia, research institutions, or industries where evidence-based decision-making is essential.

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

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

Phd Causal Inference jobs near you
Infographic showing various Phd Causal Inference job openings in Deerfield, IL as of June 2026, with employment types broken down into 94% Full Time, and 6% Part Time. Highlights an 92% Physical, 3% Hybrid, and 5% Remote job distribution, with an average salary of $125,010 per year, or $60.1 per hour.

Principal Economist, GTM Science

Everpure

Chicago, IL • On-site

Full-time

Re-posted 28 days ago

Job description

Job Summary:
Everpure is reshaping the data storage industry and is seeking a Principal Economist to drive go-to-market efficiency through advanced statistical methodologies. This role involves leading causal measurement science efforts, collaborating with various executives, and transforming large datasets into actionable insights.
Responsibilities:
• Own the Go-To-Market Causal Measurement Strategy: Architect and execute the long-term roadmap for measuring sales incrementality, partnering with senior Sales, Finance, and Operations executives to deliver highly accurate, actionable insights that guide global investment decisions.
• Design and Deploy Advanced Causal Models: Build, validate, and scale state-of-the-art observational models (such as causal forests, panel methods, and uplift models) in R or Python to isolate true headcount-driven lift and incentive plan performance from external market demand and noise.
• Drive Investment ROI and Strategic Allocation: Quantify the incremental impact of sales headcount, incentive modifications, and customer-facing programs (e.g., proofs of concept, workshops) for executive leaders (CFO, CRO, CMO) to directly influence headcount planning, NRR growth, and resource allocation.
• Operationalize Production-Grade Data Pipelines: Partner with Data Engineering, Analytics, and GTM Operations to establish robust, stable, and maintainable pipelines and data infrastructure, translating complex econometrics into automated dashboards and reusable frameworks for continuous business planning.
Qualifications:
Required:
• Advanced Econometric & Causal Inference Expertise: Deep grounding in causal inference methodologies, including causal forests, treatment-effect heterogeneity, synthetic control, and difference-in-differences analyses.
• Statistical Computing Fluency: Advanced proficiency in R, Python, or comparable statistical computing environments (such as causalTree, EconML, or statsmodels) to write clean, repeatable, and production-ready code.
• Data Engineering & Production Deployment Experience: Demonstrated capability to architect, deploy, and scale production-grade causal analyses utilizing messy, complex business datasets (such as CRM, financial systems, or telemetry data) in partnership with data engineering teams.
• Executive-Level Communication & Stakeholder Influence: Exceptional capacity to translate complex econometric and statistical results into clear narratives and strategic recommendations for non-technical corporate leaders.
Preferred:
• PhD in Economics, Econometrics, or an equivalent quantitative discipline, such as Applied Economics or Quantitative Marketing
Company:
We are Everpure. We don’t just store data—we bring it to life. Founded in , the company is headquartered in , , with a team of 5001-10000 employees. The company is currently Late Stage.

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