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Manager Causal Inference Jobs in Bellflower, CA (NOW HIRING)

YO AI Labs

Data Scientist

Glendale, CA

Proven ability to manage end-to-end experimentation and causal inference analyses, from initial requirements to impactful outcomes * Advanced skills in Python and/or R-including development of ...

YO AI Labs

Data Scientist

Glendale, CA

Proven ability to manage end-to-end experimentation and causal inference analyses, from initial requirements to impactful outcomes * Advanced skills in Python and/or R-including development of ...

Apple Inc.

Applied Scientist

Culver City, CA · On-site

$150 - $210/hr

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 ...

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 ...

CookUnity

Director, Data Science/ML

Los Angeles, CA · On-site

Develop causal inference methodologies to understand true incrementality of product changes ... roles managing data scientists or ML engineers * Proven track record building and deploying ML ...

ZipRecruiter

Decision Scientist II, Mobile

Santa Monica, CA · On-site +1

$130K - $155K/yr

... management, engineering, and design to shape and optimize the mobile user experience across ... You will leverage rigorous analysis, experimentation, and causal inference to evaluate product ...

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Manager Causal Inference information

See Bellflower, CA salary details

$30.3K

$109.3K

$123.3K

How much do manager causal inference jobs pay per year?

As of Aug 23, 2026, the average yearly pay for manager causal inference in Bellflower, CA is $109,279.00, according to ZipRecruiter salary data. Most workers in this role earn between $119,100.00 and $121,700.00 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.

What are the most commonly searched types of Causal Inference jobs in Bellflower, CA?

The most popular types of Causal Inference jobs in Bellflower, CA are:

What cities near Bellflower, CA are hiring for Manager Causal Inference jobs?

Cities near Bellflower, CA with the most Manager Causal Inference job openings:

Manager Causal Inference jobs near you
Infographic showing various Manager Causal Inference job openings in Bellflower, CA as of August 2026, with employment types broken down into 87% Full Time, 12% Part Time, and 1% Contract. Highlights an 84% Physical, 3% Hybrid, and 13% Remote job distribution, with an average salary of $109,279 per year, or $52.5 per hour.

Data Scientist

YO AI Labs

Glendale, CA

Full-time

Re-posted 21 days ago

Job description

Job Description

  • Job title: Data Scientist
  • Experience: 5-15 Years
  • Location: Glendale, USA
  • Job Type: Full-time


Must Haves:

  • Python Machine Learning, data science, AWS, Statistical Modeling, Semantic Search, Vector DB, GenAI, SQL

Qualifications:

  • Bachelors in Statistics, Economics, Computer Science, Engineering, Mathematics, Physics, or a related field + 7 years of experience with an emphasis on experimentation or causal inference.
  • Strong background in statistical modelling: regression, classification, time series forecasting, causal inference, and other techniques.
  • Robust knowledge of causal inference approaches such as propensity scores, synthetic controls, difference-in-differences, doubly robust methods, meta learners, and uplift modeling.
  • Expertise in A/B test design, execution, statistical modeling, and sophisticated causal inference techniques.
  • Proficient in conducting sample size calculations, power analysis, and minimum detectable effect estimation.
  • Experience managing multiple testing scenarios and controlling false discovery rates.
  • Ability to deploy both Bayesian and frequentist statistical approaches.
  • Deep understanding of assumptions required for causal inferences, including the foundational statistical concepts that underpin the approaches.
  • Proven ability to manage end-to-end experimentation and causal inference analyses, from initial requirements to impactful outcomes
  • Advanced skills in Python and/or R-including development of statistical analysis packages, and use of ML frameworks (e.g., scikit-learn, LGBM).
  • Strong communication skills for translating complex data into actionable narratives and presenting confidently to technical and non-technical audiences, including senior executives.

Key Responsibilities:

  • Design and Execute Experiments: Lead end-to-end A/B testing initiatives and Geo Experiments, from hypothesis formation and experimental design to statistical analysis and business recommendations.
  • Advanced Statistical & Causal Inference: Apply deep knowledge of experimental design, regression, classification, causal inference and ensure proper assumptions.
  • Build Scalable Solutions: Develop experimentation and causal inference tools and frameworks that can scale across Disney's businesses.
  • Deliver Strategic Insights: Partner with stakeholders to identify optimization opportunities and translate complex analytical findings into clear business recommendations.
  • Influence Executive Decisions: Present findings and recommendations to senior leadership, effectively communicating statistical concepts to non-technical stakeholders.


Preferred Qualifications:

  • MS in computer science, statistics, math or a related quantitative field +5 years of relevant experience OR PhD + 3 years of relevant experience with an emphasis on experimentation or causal inference.
  • Experience with ETL and data engineering: data extraction, transformation, integration, and quality controls for analytics at scale.
  • Skilled in production deployment and monitoring of data science solutions, including CI/CD pipelines, automated reporting, and ongoing experiment/model monitoring.
  • Familiarity with data platforms and applications such as Databricks, Jupyter, Snowflake, and Github.
  • Strong strategic business insight, preferably in subscription-based business models, with ability to apply experimentation and analytics to market trends and consumer insights.
  • Proven track record of leadership and stakeholder/project management, including influencing cross-functional teams and delivering high-impact outcomes.
  • Adept at adapting quickly to shifting priorities in a fast-moving environment while maintaining quality.
  • Drive and maintain a culture of quality, innovation and experimentation.
  • Demonstrated experience mentoring colleagues on best practices and technical concepts for building large scale solutions.