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Causal Inference Machine Learning Postdoctoral Jobs in Pasadena, CA

... causal inference models, conduct statistical/machine learning analyses, or design experiments to measure the value of the business and its many features - Partner closely with Business, Finance ...

New

... causal inference models, conduct statistical/machine learning analyses, or design experiments to measure the value of the business and its many features - Partner closely with Business, Finance ...

New

... modeling, causal inference, uplift modeling, and media mix modeling - to improve marketing ... Proven experience building predictive models and applying machine learning techniques to solve ...

New

... inference, labeling, and evaluation • Judiciously combine open-source solutions and novel ... Machine Learning, including ownership of projects throughout the entire ML Lifecycle • ...

... inference, labeling, and evaluation • Judiciously combine open-source solutions and novel ... Machine Learning, including ownership of projects throughout the entire ML Lifecycle • ...

Senior Data Scientist

Los Angeles, CA · On-site

$106.31 - $132.31/hr

This role blends rigorous experimentation, applied machine learning, and strategic insight ... Strong foundation in causal inference and experimentation, including advanced methods beyond ...

Machine Learning Engineer

Torrance, CA · On-site

$160K - $250K/yr

Work in every facet of the Machine Learning lifecycle - including the creation and optimization of production data pipelines, and software systems for training, inference, labeling, and evaluation

... causal inference models, conduct statistical/machine learning analyses, or design experiments to ... in a postdoctoral position, consulting position, government position or academic research ...

New

Build machine learning systems from the ground up and design scalable data science infrastructure ... causal inference to ensure the reliability of analytical insights and model impact evaluation.

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Causal Inference Machine Learning Postdoctoral information

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$38.7K

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$66.5K

How much do causal inference machine learning postdoctoral jobs pay per year?

As of Jul 15, 2026, the average yearly pay for causal inference machine learning postdoctoral in Pasadena, CA is $59,147.00, according to ZipRecruiter salary data. Most workers in this role earn between $58,400.00 and $61,600.00 per year, depending on experience, location, and employer.

What is a Causal Inference Machine Learning Postdoctoral researcher?

A Causal Inference Machine Learning Postdoctoral researcher is a scientist who specializes in developing and applying machine learning methods to understand cause-and-effect relationships in data. They typically hold a recent PhD in statistics, computer science, economics, or a related field, and work in academic or industry research settings. Their work involves designing experiments, analyzing complex datasets, and creating models that can infer causal relationships, which are crucial for making robust predictions and informed decisions. This role often collaborates with interdisciplinary teams to apply these techniques to domains such as healthcare, social science, or economics.

What are the key skills and qualifications needed to thrive as a Causal Inference Machine Learning Postdoctoral researcher, and why are they important?

To thrive as a Causal Inference Machine Learning Postdoctoral researcher, you need a strong background in statistics, causal inference methodologies, and advanced machine learning, usually evidenced by a PhD in a relevant field. Familiarity with programming languages such as Python or R, experience using statistical software (e.g., TensorFlow, PyTorch, Stan), and knowledge of causal inference libraries are typically required. Outstanding analytical thinking, problem-solving abilities, and strong communication skills help you collaborate effectively and explain complex concepts to diverse audiences. These skills and qualifications are vital for advancing research, deriving actionable insights from data, and contributing to impactful scientific discoveries.

What are some common challenges faced by Causal Inference Machine Learning Postdoctoral researchers when integrating causal models with real-world data?

Causal Inference Machine Learning Postdoctoral researchers often encounter challenges such as dealing with unobserved confounding variables, ensuring data quality, and addressing biases inherent in observational datasets. Integrating advanced machine learning techniques with causal inference frameworks requires careful consideration of model assumptions and validation methods. Collaboration with domain experts is essential to properly interpret results and to translate findings into actionable insights, especially in interdisciplinary settings like healthcare or social sciences.

What is the difference between Causal Inference Machine Learning Postdoctoral vs Data Scientist?

AspectCausal Inference Machine Learning PostdoctoralData Scientist
Required CredentialsPhD in statistics, machine learning, or related fieldBachelor's or Master's in data science, computer science, or related field
Work EnvironmentAcademic research, research labs, universitiesCorporate, tech companies, startups
Industry UsageResearch, academia, specialized industry projectsBusiness analytics, product development, data-driven decision making
Common Search/ComparisonYesYes

The main difference is that Causal Inference Machine Learning Postdoctoral roles focus on academic research and developing new methods in causal inference, often requiring a PhD. Data Scientists typically work in industry, applying existing models to solve business problems, with a focus on data analysis and visualization. While both roles involve machine learning, the postdoctoral position emphasizes research and theory, whereas data science emphasizes practical application.

What are popular job titles related to Causal Inference Machine Learning Postdoctoral jobs in Pasadena, CA? For Causal Inference Machine Learning Postdoctoral jobs in Pasadena, CA, the most frequently searched job titles are:
What job categories do people searching Causal Inference Machine Learning Postdoctoral jobs in Pasadena, CA look for? The top searched job categories for Causal Inference Machine Learning Postdoctoral jobs in Pasadena, CA are:
What cities near Pasadena, CA are hiring for Causal Inference Machine Learning Postdoctoral jobs? Cities near Pasadena, CA with the most Causal Inference Machine Learning Postdoctoral job openings:
Postdoctoral Scholar in the UCLA Tanigawa Lab

Postdoctoral Scholar in the UCLA Tanigawa Lab

University of California, Los Angeles

Los Angeles, CA • On-site

Other

Re-posted yesterday


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Job description

Position description
Are you passionate about using your skills in biomedical data science, statistical modeling, or human genetics to make a real-world impact on human health? The Tanigawa Lab at UCLA is seeking a highly motivated, exceptionally creative researcher to join our new lab.
Our group investigates disease heterogeneity: why individuals differ in disease onset, progression, and treatment response. We develop statistical models and computational tools to uncover the mechanistic basis of inter-individual variation in the disease. Our long-term goal is to provide more tailored prevention and treatment strategies for everyone.
Postdoctoral Scholars recruited for this position (JPF11031) will work closely with Prof. Tanigawa on a mutually agreed-upon interdisciplinary project focused on representation learning for computational dissection of disease heterogeneity.
The position is available immediately, and the start date is negotiable. The initial appointment is two years, with the potential for renewal subject to satisfactory progress.
A mutual fit between the advisor and the trainee is critical to ensuring that your time in the lab is productive and rewarding. Before you apply, please carefully read our lab website to learn about our research interests, mentoring philosophy, and expectations for application materials.
Lab: Tanigawa Lab
Contact: joinus@tanigawalab.org
Lab: https://tanigawalab.org/
Qualifications
Basic qualifications
Ph.D. or equivalent in Biomedical Data Science or a closely related discipline at date of hire.
Additional qualifications
Highly motivated candidates with demonstrated evidence of research creativity are encouraged to apply.
Essential qualifications for this position include:
• Proficiency in programming languages (e.g., Python or R);
• Strong quantitative skills with a basic familiarity with statistical inference; and
• Excellent scientific communication skills (both oral and written)
Additional qualifications suitable for this position include:
• Familiarity with representation learning (e.g., variational autoencoders);
• Experience with analyzing large-scale real-world datasets; or
• Familiarity with causal inference techniques in human genetics (e.g., Mendelian Randomization)
Application Requirements
Document requirements
  • Curriculum Vitae - Your most recently updated C.V.
  • Cover Letter
  • Statement of Research
  • Statement of Teaching (Optional)
  • Reference check authorization release form - Complete and upload the reference check authorization release form

Reference requirements
  • 3-5 required (contact information only)

Shortlisted applicants should arrange for recommendation letters to be sent from at least three references.
Apply link: https://recruit.apo.ucla.edu/JPF11031
Help contact: tanigawa@ucla.edu
About UCLA
As a University employee, you will be required to comply with all applicable University policies and/or collective bargaining agreements, as may be amended from time to time. Federal, state, or local government directives may impose additional requirements.
The University of California is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, protected veteran status, or other protected status under state or federal law.
As a condition of employment, the finalist will be required to disclose if they are subject to any final administrative or judicial decisions within the last seven years determining that they committed any misconduct.
  • "Misconduct" means any violation of the policies or laws governing conduct at the applicant's previous place of employment, including, but not limited to, violations of policies or laws prohibiting sexual harassment, sexual assault, or other forms of harassment, discrimination, dishonesty, or unethical conduct, as defined by the employer.
  • UC Sexual Violence and Sexual Harassment Policy
  • UC Anti-Discrimination Policy for Employees, Students and Third Parties
  • APM - 035: Affirmative Action and Nondiscrimination in Employment

Job location
Los Angeles, CA

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