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Manager Causal Inference Jobs (NOW HIRING)

Apple Inc.

Applied Scientist

Culver City, CA · On-site

Dive deep into large‑scale data sources to uncover opportunities for Causal Inference automation, predictive methods, and quantitative modeling. * Collaborate with product managers, data scientists ...

Hudson Manpower

Data Scientist

Cincinnati, OH · On-site

$55 - $60/hr

The ideal candidate will have hands-on experience applying causal inference and econometric ... Experience with MLOps, deployment, orchestration, monitoring, and model lifecycle management.

Apple

Applied Scientist

Austin, TX · On-site

$175K - $308K/yr

Dive deep into large-scale data sources to uncover opportunities for Causal Inference automation, predictive methods, and quantitative modeling. Collaborate with product managers, data scientists ...

Apple

Applied Scientist

Austin, TX

$175K - $308K/yr

Dive deep into large-scale data sources to uncover opportunities for Causal Inference automation, predictive methods, and quantitative modeling. Collaborate with product managers, data scientists ...

Roku

Senior Research Data Scientist

Boston, MA · On-site

$330K - $375K/yr

What you'll be doing * Design, build, and productionize a causal inference platform that ... Work cross-functionally with Data Engineering, Product Management, and Core Analytics to translate ...

Roku, Inc.

Sr. Research Data Scientist

Boston, MA · On-site

$330K - $375K/yr

What you'll be doing * Design, build, and productionize a causal inference platform that ... Work cross-functionally with Data Engineering, Product Management, and Core Analytics to translate ...

Roku

Senior Research Data Scientist

San Jose, CA · On-site

$330K - $375K/yr

What you'll be doing * Design, build, and productionize a causal inference platform that ... Work cross-functionally with Data Engineering, Product Management, and Core Analytics to translate ...

Roku

Senior Research Data Scientist

New York, NY · On-site

$330K - $375K/yr

What you'll be doing * Design, build, and productionize a causal inference platform that ... Work cross-functionally with Data Engineering, Product Management, and Core Analytics to translate ...

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Manager Causal Inference information

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$29K

$104.6K

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How much do manager causal inference jobs pay per year?

As of Sep 13, 2026, the average yearly pay for manager causal inference in the United States is $104,575.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,000.00 and $116,500.00 per year, depending on experience, location, and employer.

What does a manager causal inference do?

A Manager Causal Inference leads teams that analyze data to determine cause-and-effect relationships, often in business, healthcare, or technology settings. They design experiments or use statistical methods to understand how different factors influence outcomes, helping organizations make data-driven decisions. This role typically involves managing projects, overseeing analysts or data scientists, and communicating findings to stakeholders. Strong expertise in statistics, data analysis, and leadership is essential for success in this position.

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

To thrive as a Manager of Causal Inference, you need a deep understanding of statistics, econometrics, and experimental design, typically supported by an advanced degree in a quantitative field. Proficiency with data analysis tools such as R, Python, SQL, and specialized causal inference libraries, along with experience using data visualization and project management platforms, is crucial. Strong leadership, communication, and critical thinking skills help you effectively guide teams and translate complex findings to stakeholders. These skills ensure rigorous, actionable insights that drive strategic decision-making and organizational impact.

How does a manager causal inference typically collaborate with cross-functional teams to drive impactful business insights?

Managers of Causal Inference frequently work alongside data scientists, product managers, engineers, and business leaders to design and execute experiments that reveal the true impact of business decisions. They translate complex statistical findings into actionable recommendations, ensuring stakeholders understand both the methodology and implications. Regularly, they lead discussions on experiment design, data collection strategies, and result interpretation, fostering a culture of evidence-based decision-making across the organization.
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Manager Causal Inference jobs near you
Infographic showing various Manager Causal Inference job openings in the United States as of September 2026, with employment types broken down into 86% Full Time, 13% Part Time, and 1% Contract. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution, with an average salary of $104,575 per year, or $50.3 per hour.

Engineering Manager Experimentation - amplitude

San Francisco, CA • On-site

Polluxa, Inc.
See more jobs at Polluxa, Inc.external

$200 - $250/hr

Other

This job post has expired 4 days ago. Applications are no longer accepted.

Job description

ABOUT THE ROLE

& TEAM

We’re looking for an Engineering Manager to lead the Data Infrastructure team within Statsig Experiment at Amplitude. You will lead a multidisciplinary team of software engineers, data engineers, and data scientists responsible for the systems that power experimentation at scale.

The team owns three critical areas:

  • Data ingestion: Collecting and importing experiment exposures, custom events, OpenTelemetry data, and real user monitoring data across SDKs, streaming systems, cloud storage, and customer data warehouses.
  • Data computation: Building distributed computation systems that transform raw data into accurate, timely experiment results.
  • Stats engine: Developing and productionizing the statistical methods that help customers make trustworthy decisions from their experiments.

This is not a traditional data engineering management role. We are looking for a leader with a solid data science and statistical foundation who can connect advances in experimentation methodology with scalable production systems. You will help set our technical and scientific direction, translating new statistical methods and machine learning research into capabilities that customers can use reliably at scale.

You’ll partner closely with data scientists, engineers, product managers, and customers to advance the state of experimentation. The ideal candidate is equally comfortable discussing causal inference and statistical power with data scientists, distributed computation architectures with engineers, and experimentation strategy with customers.

WHAT YOU’LL DO
  • Lead and grow the team responsible for Statsig’s data ingestion, experiment computation, and stats engine.
  • Define the technical and scientific strategy for advancing experimentation across both Statsig Cloud and warehouse-native deployments.
  • Partner with data scientists and engineers to turn new statistical and causal inference methods into scalable, reliable product capabilities.
  • Evolve our data and computation architecture to support increasingly complex experiment designs, metrics, and customer datasets.
  • Engage with customers to understand their experimentation challenges and translate them into platform and methodology improvements.

YOU’LL BE A GREAT ADDITION TO THE TEAM IF YOU HAVE

  • A strong data science background, with hands‑on experience in experimentation, statistics, or causal inference. Experience solely in data engineering is not sufficient for this role.
  • Experience leading teams (10-15 team members) that build and productionize statistically rigorous, data-intensive products.
  • Familiarity with experimentation methods such as variance reduction, sequential testing, Bayesian inference, causal effects modeling, or heterogeneous treatment effects.
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