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Manager Causal Inference Jobs in California (NOW HIRING)

Anthropic

Data Scientist, Supply

San Francisco, CA · On-site

The second is a causal-inference problem: there are many levers - rate limits, pricing, cache ... without formal management responsibility Equal Opportunity Anthropic is an equal opportunity ...

Intuit

Senior Staff AI Research Scientist

San Diego, CA · On-site

$226K - $306K/yr

Conduct original research in decision-focused AI, probabilistic modeling, causal inference ... management Footer Intuit provides a competitive compensation package with a strong pay for ...

Intuit

Senior Staff AI Research Scientist

Mountain View, CA · On-site

$116K - $148K/yr

Conduct original research in decision-focused AI, probabilistic modeling, causal inference ... business management Intuit provides a competitive compensation package with a strong pay for ...

Tubi

Data Scientist, Growth Analytics

Los Angeles, CA · On-site +1

Deep understanding of experimentation methodologies, including A/B testing, causal inference ... to manage all personal matters. * For all full-time, regular employees, in lieu of FOX Paid ...

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Manager Causal Inference information

How does a Manager of 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.

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 of Causal Inference, and why are they important?

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.
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Manager Causal Inference jobs near you

Principal Economist, GTM Science

Everpure

Santa Clara, CA

Other

PTO

Posted 26 days ago

Job description

THE ROLE

Everpure is seeking a Principal Economist to drive go-to-market (GTM) efficiency by leading our causal measurement science vision. You will lead the development of advanced statistical methodologies to measure the incrementality of sales headcount, incentive investments, and customer-facing activities (e.g. workshops, proofs of concept, enablement collateral, events). 

In this high-impact role, you will pioneer advanced statistical frameworks that separate true sales-driven lift from market noise, directly shaping global headcount planning and incentive designs. Collaborating closely with executive GTM Finance, Data Science, and Sales leadership, you will transform massive datasets into production-grade science deliverables that maximize global revenue and optimize ROI.

WHAT YOU'LL DO

  • 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.

WHAT YOU BRING

  • PhD in Economics, Econometrics, or an equivalent quantitative discipline, such as Applied Economics or Quantitative Marketing, preferred. 
  • 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.
  • Location: We are primarily an in-office environment and therefore, you will be expected to work from the Santa Clara, CA office in compliance with Everpure's policies, unless you are on PTO, or work travel, or other approved leave.

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