ZipRecruiter

Log In

1

Director Causal Inference Jobs (NOW HIRING)

AT and T

Director-Advanced Analytics

Dallas, TX · On-site

The Director, Advanced Analytics sits at the forefront of AT&T's transformation into a truly ... By integrating Marketing Mix Models (MMM), causal inference, experimentation, predictive analytics ...

AT&T

Director-Advanced Analytics

Dallas, TX · On-site

The Director, Advanced Analytics sits at the forefront of AT&T's transformation into a truly ... By integrating Marketing Mix Models (MMM), causal inference, experimentation, predictive analytics ...

Intuit

Senior Data Scientist

Mountain View, CA

$149K - $202K/yr

Causal Inference: Lead causal inference and econometric analyses to understand and influence key ... Deliver compelling, data-driven narratives to VP and Director stakeholders; distill complex ...

Intuit

Senior Data Scientist

San Diego, CA

$149K - $202K/yr

Causal Inference: Lead causal inference and econometric analyses to understand and influence key ... Deliver compelling, data-driven narratives to VP and Director stakeholders; distill complex ...

Intuit Inc.

Senior Data Scientist

San Diego, CA · On-site

$120 - $160/hr

Causal Inference: Lead causal inference and econometric analyses to understand and influence key ... Deliver compelling, data-driven narratives to VP and Director stakeholders; distill complex ...

Zocdoc

Director, Marketing Data Science

New York, NY · On-site +1

As Director, Marketing Data Science, you'll own the measurement strategy that determines how Zocdoc ... You follow how the field is evolving (privacy changes, signal loss, new causal inference approaches ...

Intuit

Senior Data Scientist

San Diego, CA

$149K - $202K/yr

Causal Inference: Lead causal inference and econometric analyses to understand and influence key ... Deliver compelling, data-driven narratives to VP and Director stakeholders; distill complex ...

Intuit

Senior Data Scientist

Mountain View, CA · On-site

$149K - $202K/yr

Causal Inference: Lead causal inference and econometric analyses to understand and influence key ... Deliver compelling, data-driven narratives to VP and Director stakeholders; distill complex ...

Intuit

Senior Data Scientist

San Diego, CA · On-site

$149K - $202K/yr

Causal Inference: Lead causal inference and econometric analyses to understand and influence key ... Deliver compelling, data-driven narratives to VP and Director stakeholders; distill complex ...

next page

Showing results 1-20

All JobsScience JobsResearch JobsStatistician JobsDirector Causal Inference Jobs

Director Causal Inference information

What cities are hiring for Director Causal Inference jobs?

Cities with the most Director Causal Inference job openings:

What are the most commonly searched types of Causal Inference jobs?

The most popular types of Causal Inference jobs are:

What states have the most Director Causal Inference jobs?

States with the most job openings for Director Causal Inference jobs include:

What job categories do people searching Director Causal Inference jobs look for?

The top searched job categories for Director Causal Inference jobs are:

Director Causal Inference jobs near you
Infographic showing various Director Causal Inference job openings in the United States as of August 2026, with employment types broken down into 93% Full Time, 2% Part Time, and 5% Contract. Highlights an 74% In-person, 2% Hybrid, and 24% Remote job distribution.

Staff Data Scientist - Experimentation & Causal Inference

HighLevel

Remote

Full-time

Posted 28 days ago

Job description

About HighLevel:
HighLevel is an AI-powered business operating system that gives agencies, entrepreneurs and SMBs the infrastructure to build, automate and scale. Today, HighLevel supports SMBs across 150+ countries, fueling community-driven growth rooted in real customer outcomes.
To date, businesses operating on HighLevel have generated over $7 billion in ecosystem value, demonstrating the impact of shared infrastructure at scale. By centralizing conversations, automation and intelligence into one system, we help businesses move faster, reduce complexity and execute efficiently.
Behind the platform, HighLevel powers more than 4 billion API hits and 2.5 billion message events daily. With 250 terabytes of distributed data, 250+ microservices and over 1 million domain names supported, our architecture is built for performance, resilience and long-term scalability.
Our People
With over 2,000 team members across 10+ countries, HighLevel operates as a global, remote-first organization built for speed and ownership. We value initiative, clarity and execution, creating space for ambitious people to build systems that support millions of businesses worldwide. Here, innovation thrives, ideas are celebrated and people come first, no matter where they call home.
Our Impact
Every month, HighLevel enables more than 1.5 billion messages, 200 million leads and 20 million conversations for the more than 1 million businesses we support. Behind those numbers are real people building independence, expanding opportunity and creating measurable impact. We're proud to be a part of that.
Learn more about us on our YouTube Channel or Blog Posts.
About the Role:
We're hiring our first Staff Data Scientist, Experimentation & Causal Inference to define how HighLevel learns from experiments and turns results into trustworthy product decisions and business strategy. Our teams ship fast and have started experimenting to make data-backed decisions; you'll bring the rigor and consistency to scale that across the company.
You'll set the company-wide standard for experiment design and causal inference, embed it in how the product gets built, and coach PMs and analysts to run tests that hold up. You'll do this in a fast-moving, multi-product SaaS/CRM environment where samples are small, many products move at once, and a wrong "win" is costly. This is a founding, hands-on IC role with executive sponsorship and a path to build out a Data Science team as the function matures.
Responsibilities:
  • Define the end-to-end methodology every team follows - hypothesis - metrics - design - power - readout - decision - and make it the default
  • Own the statistical approach (significance, multiple comparisons, sequential testing, variance reduction like CUPED) for small-sample, fast-paced contexts where classic A/B power is hard to reach
  • Build the methods toolkit for our clustered, hierarchical data (user - sub-account/location - agency), where randomization and analysis units differ
  • Apply rigorous causal inference (matching, diff-in-diff, instrumental variables, synthetic control, etc) when clean experiments aren't feasible - churn, onboarding, GTM - separating real signal from selection bias, seasonality, and mix effects
  • Own the design discipline for running many experiments at once - layering, orthogonal experiments, holdouts, and guardrails that keep concurrent tests from contaminating each other
  • Partner with AI/ML teams to design and evaluate experiments for AI features, including measurement for non-deterministic, fast-iterating systems
  • Run the experiment review forum and hold the line on what counts as a real result
  • Build the Experimentation curriculum and templates that level up PMs and analysts so good design scales beyond you
  • Partner with Analytics Engineering on governed, experiment-ready data and consistent metric definitions
  • Influence leadership and cross-functional partners on where to invest, translating statistical nuance into clear, decision-grade guidance

Requirements:
  • 9+ years in data science, product analytics, or applied statistics, with deep hands-on experience designing and analyzing online controlled experiments at scale
  • Strong applied statistics - frequentist foundations, Bayesian methods, power analysis, variance reduction, and the failure modes of A/B testing (peeking, multiple testing, network/cluster effects)
  • Practical causal inference, with sound judgment about when a result is causal versus an artifact of how the data was generated
  • Experience in small-sample, fast-paced, multi-product environments -you know when a decision needs a clean experiment and when it needs a fast, good-enough read
  • Strong SQL and working proficiency in Python or R
  • Cross-functional and senior-leadership influence - you raise others' experiment quality without direct authority

Nice to Have:
  • Familiarity with a modern experimentation platform such as Statsig
  • Experience building an experimentation practice or culture from the ground up
  • Background in B2B SaaS, CRM, or product-led growth, and familiarity with the measurement challenges these motions create
  • Multi-tenant or marketplace product experience (agency - sub-account - end-customer structures)

$163,400 - $220,000 a year
EEO Statement:
The company is an Equal Opportunity Employer. As an employer subject to affirmative action regulations, we invite you to voluntarily provide the following demographic information. This information is used solely for compliance with government recordkeeping, reporting, and other legal requirements. Providing this information is voluntary and refusal to do so will not affect your application status. This data will be kept separate from your application and will not be used in the hiring decision.
We encourage you to review our Privacy Policy before submitting your application
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Apply