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Phd Causal Inference Jobs (NOW HIRING)

Twitch

Data Scientist

New York, NY · On-site

OR a PhD in Economics, Statistics, Computer Science, or related quantitative field * Proficiency in SQL * Proficiency with Python or R * Strong foundation in experimentation and causal inference ...

New

Apple

Applied ML Science Manager

Cupertino, CA

$206K - $356K/yr

You will be at the forefront of designing, developing, and deploying cutting-edge Causal Inference ... PhD in related field Hands-on experience leveraging Generative AI to improve productivity and ...

Twitch

Data Scientist

Seattle, WA · On-site

OR a PhD in Economics, Statistics, Computer Science, or related quantitative field * Proficiency in SQL * Proficiency with Python or R * Strong foundation in experimentation and causal inference ...

New

Apple

Applied Scientist

Austin, TX · On-site

You will be at the forefront of designing, developing, and deploying cutting-edge Causal Inference ... PhD in related field Hands-on experience leveraging Generative AI to improve productivity and ...

Apple

Applied ML Science Manager

Cupertino, CA · On-site

You will be at the forefront of designing, developing, and deploying cutting-edge Causal Inference ... PhD in related field Hands-on experience leveraging Generative AI to improve productivity and ...

Intuit

Staff Data Scientist

San Diego, CA · On-site

$185K - $251K/yr

Causal Inference: Lead causal inference and econometric analyses to understand and influence key ... Qualifications Master's or PhD degree in Computer Science, Statistics, Econometrics, Data Science ...

Lennar

Lead Data Scientist

Boston, MA · On-site

Design and run experiments (A/B tests, multi-armed bandits, uplift modeling, causal inference) and ... Advanced degree (MS/PhD) preferred. * 7+ years of applied data science experience (5+ with MS, 3+ ...

Intuit

Staff Data Scientist

San Diego, CA

$185K - $251K/yr

Causal Inference: Lead causal inference and econometric analyses to understand and influence key ... Qualifications Master's or PhD degree in Computer Science, Statistics, Econometrics, Data Science ...

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 ...

Intuit

Staff Data Scientist

Mountain View, CA · On-site

$185K - $251K/yr

Causal Inference: Lead causal inference and econometric analyses to understand and influence key ... Qualifications Master's or PhD degree in Computer Science, Statistics, Econometrics, Data Science ...

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Phd Causal Inference information

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$40K

$122.9K

$178.5K

How much do phd causal inference jobs pay per year?

As of Jul 10, 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.
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What cities are hiring for Phd Causal Inference jobs? Cities with the most Phd Causal Inference job openings:
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Phd Causal Inference jobs near you
Infographic showing various Phd Causal Inference job openings in the United States as of July 2026, with employment types broken down into 88% Full Time, 11% Part Time, and 1% Contract. Highlights an 84% Physical, 2% Hybrid, and 14% Remote job distribution, with an average salary of $122,928 per year, or $59.1 per hour.
Data Scientist

Data Scientist

Twitch

New York, NY • On-site

Other

Medical, Dental, Vision, Retirement, PTO

Posted 2 days ago

New

Job description

About Us

Twitch is the world's biggest live streaming service, with global communities built around gaming, entertainment, music, sports, cooking, and more. It is where thousands of communities come together for whatever, every day.

We're about community, inside and out. You'll find coworkers who are eager to team up, collaborate, and smash (or elegantly solve) problems together. We're on a quest to empower live communities, so if this sounds good to you, see what we're up to on LinkedIn and X,  and discover the projects we're solving on our Blog. Be sure to explore our Interviewing Guide to learn how to ace our interview process.

About the Role

Join the Monetization team at Twitch, where we build the products that help creators make a living on the platform. You'll work on products like Subscriptions, Bits, and Gifting, and the pricing and packaging decisions behind them. 

You'll partner closely with product, engineering, finance, and data teams to measure the impact of new features, design and analyze experiments, and apply causal inference methods to inform decisions where A/B testing isn't possible. The work ranges from high-velocity experimentation on consumer-facing products to deeper pricing, policy, and segmentation analyses where causal identification is the central challenge.

This role is well-suited for someone with a strong economics or causal ML foundation who wants to apply rigorous statistical thinking to real product decisions at scale. You'll need to be comfortable writing SQL, working with imperfect data, and partnering with stakeholders to turn analysis into product impact. Our team is based at Twitch HQ in San Francisco, CA.

You can work in San Francisco, CA; New York, NY; or Seattle, WA 

You Will:
  • Apply causal inference methods where experimentation isn't feasible
  • Develop models and analyses that inform pricing, segmentation, and revenue optimization
  • Design, run, and analyze A/B experiments 
  • Partner with product, engineering, and finance to translate ambiguous business questions into measurement frameworks
  • Build and maintain dashboards, reporting, and analytical tooling that support ongoing decision-making
You Have:
  • 3+ years of experience as a data scientist, applied scientist, economist, or related field; OR a PhD in Economics, Statistics, Computer Science, or related quantitative field
  • Proficiency in SQL
  • Proficiency with Python or R
  • Strong foundation in experimentation and causal inference, including A/B test design and quasi-experimental methods
  • Strong communication skills across technical and non-technical stakeholders
  • Comfort building dashboards and recurring reporting
Bonus Points
  • Master's or PhD in Economics, Statistics, or a related quantitative field
  • Industry experience working on consumer products with high transaction volume (subscriptions, marketplaces, payments) 
  • Hands-on experience with Airflow, SageMaker, or deploying ML models in production
  • Familiarity with modern causal ML methods (double ML, causal forests, heterogeneous treatment effects)
Perks
  • Medical, Dental, Vision & Disability Insurance
  • 401(k)
  • Maternity & Parental Leave
  • Flexible PTO
  • Amazon Employee Discount

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. 

Job ID: TW9226

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