ZipRecruiter

Log In

1

Phd Causal Inference Jobs (NOW HIRING)

Alignerr

Econometrics Instructor

Manhattan, NY · Remote

... causal inference, and quantitative analysis. Organization: Alignerr (Powered by Labelbox) Type ... Master's or PhD in Economics, Statistics, or a related quantitative field Proficiency with ...

Netflix

Machine Learning Scientist 4 - Pricing Science

$300K - $537K/yr

What You Will Do * Design and implement quasi-experimental and causal inference approaches ... You have an advanced degree (MS or PhD) in statistics, economics, computer science, mathematics, or ...

Lyft

Data Science Manager, Mapping

San Francisco, CA · On-site

Ensure robust experimentation and causal inference methodologies are applied to measure the impact ... Advanced degree (MS or PhD, PhD preferred) in a quantitative field like Operations Research ...

Apple

Staff Data Scientist

Sunnyvale, CA · On-site

... awareness PhD in Statistics, Mathematics, Data Science, ML, Physics, Engineering, Computer Science or in a quantitative fieldPublications or patents in causal inference, ML, or applied ...

Netflix

OR

$300K - $537K/yr

What You Will Do * Design and implement quasi-experimental and causal inference approaches ... You have an advanced degree (MS or PhD) in statistics, economics, computer science, mathematics, or ...

Netflix

Machine Learning Scientist 4 - Pricing Science

$300K - $537K/yr

What You Will Do * Design and implement quasi-experimental and causal inference approaches ... You have an advanced degree (MS or PhD) in statistics, economics, computer science, mathematics, or ...

Apple

Staff Data Scientist

Sunnyvale, CA

$203.30K - $305.60K/yr

Preferred Qualifications PhD in Statistics, Mathematics, Data Science, ML, Physics, Engineering, Computer Science or in a quantitative field Publications or patents in causal inference, ML, or ...

Alignerr

Econometrics Instructor

Phoenix, AZ · Remote

Strong command of regression analysis, causal inference, hypothesis testing, and statistical ... Nice to Have Master's or PhD in Economics, Statistics, or a related quantitative field. Hands‐on ...

Intuit

Senior Staff AI Research Scientist

Mountain View, CA · On-site

$116.20K - $148K/yr

Conduct original research in decision-focused AI, probabilistic modeling, causal inference ... PhD in Computer Science, Electrical Engineering, Statistics, Applied Mathematics, or a related ...

next page

Showing results 1-20

People also search for

All JobsPhd Causal Inference Jobs

Phd Causal Inference information

See salary details

$40K

$122.9K

$178.5K

How much do phd causal inference jobs pay per year?

As of May 29, 2026, the average yearly pay for phd causal inference in the United States is $122,928.00, according to ZipRecruiter salary data. Most workers in this role earn between $105,000.00 and $138,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a PhD Causal Inference researcher, and why are they important?

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.
More about Phd Causal Inference jobs
What cities are hiring for Phd Causal Inference jobs? Cities with the most Phd Causal Inference job openings:
What states have the most Phd Causal Inference jobs? States with the most job openings for Phd Causal Inference jobs include:
What job categories do people searching Phd Causal Inference jobs look for? The top searched job categories for Phd Causal Inference jobs are:
Phd Causal Inference jobs near you
Infographic showing various Phd Causal Inference job openings in the United States as of May 2026, with employment types broken down into 63% Full Time, and 37% Part Time. Highlights an 96% Physical, 3% Hybrid, and 1% Remote job distribution, with an average salary of $122,928 per year, or $59.1 per hour.
Applied Data Scientist, Unit Economics Understanding

Applied Data Scientist, Unit Economics Understanding

OpenAI

San Francisco, CA • On-site

$290K - $441K/yr

Full-time

Posted 9 days ago

Job description

About the RoleThis role focuses on building the strategic unit economics understanding of OpenAI, guiding sustainable growth to make it the most impactful company of our generation and beyond.
You will lead the development of foundational causal inference and data science models and frameworks to predict and quantify the drivers of customer lifetime value (LTV), translating deep data insights into strategic decisions and growth levers. The role requires both technical depth and executive-level communication.
This position is based in our San Francisco HQ with a hybrid work model (three days in office per week). Relocation assistance is available.
The Vision
  • Build causal inference and predictive analytics capabilities to measure and forecast LTV across customer segments (B2C and B2B), and quantify the incremental impact of different actions or product features on customer LTV.
  • Design customer "happy paths" by identifying adoption journeys that maximize lifetime value while ensuring customers gain the most from our ecosystem.
  • Analyze price elasticity to guide product packaging, monetization, and pricing strategies.

In this role, you will:
  • Partner with cross-functional teams (Finance, Product, Data Engineering, GTM, and other DS teams) to build causal inference and predictive models that drive business decisions.
  • Develop and maintain LTV models across product lines and customer cohorts.
  • Architect scalable frameworks and models that democratize economic insights for leadership and functional teams.
  • Support strategic pricing and investment decisions with robust analytical and causal evidence.
  • Lead cross-functional data science initiatives, ensuring analytical rigor, clarity, and timely delivery.

You might thrive in this role if you:
  • Executive communication - ability to distill complex analysis into clear, actionable recommendations for leadership.
  • Technical breadth - comfort spanning ROI analysis, causal inference, statistical modeling, and ML predictive models; strong experience with Python and SQL.
  • Strategic judgment - ability to connect analytical insights to business impact, delivering the "so what" that informs leadership decisions.
  • Collaboration and ownership - thrive in a fast-paced, cross-functional environment and proactively take projects from concept to delivery.

Qualifications
  • MS or PhD in a quantitative field (Statistics, Economics, Applied Math, Operations Research, Computer Science, etc.).
  • 7+ years of experience in applied data science, causal inference, or quantitative strategy.
  • Proven record of delivering high-impact insights to executive leadership.
  • Experience building scalable analytical frameworks and models that inform business decision-making.

About OpenAI
OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
For additional information, please see OpenAI's Affirmative Action and Equal Employment Opportunity Policy Statement.
Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.
To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.
We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.
OpenAI Global Applicant Privacy Policy
At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

Apply