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Causal Inference Machine Learning Postdoctoral Jobs in Missouri

Walmart

Staff, Data Scientist (Pricing)

Noel, MO · On-site

$110K - $220K/yr

Our work combines techniques from forecasting, optimization, operations research, machine learning (classical ML, deep learning, reinforcement learning), causal inference, experimentation, and ...

Walmart

(USA) Principal, Data Scientist

Anderson, MO · On-site

$110K - $220K/yr

This team leads advancements in generative AI, agentic intelligence, machine learning, measurement, and causal inference to redefine retail experiences, optimize operations, and develop new business ...

Walmart

(USA) Principal, Data Scientist

Noel, MO · On-site

$110K - $220K/yr

This team leads advancements in generative AI, agentic intelligence, machine learning, measurement, and causal inference to redefine retail experiences, optimize operations, and develop new business ...

Walmart

Staff, Data Scientist (Pricing)

Cassville, MO · On-site

$110K - $220K/yr

Our work combines techniques from forecasting, optimization, operations research, machine learning (classical ML, deep learning, reinforcement learning), causal inference, experimentation, and ...

Walmart

Staff, Data Scientist (Pricing)

Anderson, MO · On-site

$110K - $220K/yr

Our work combines techniques from forecasting, optimization, operations research, machine learning (classical ML, deep learning, reinforcement learning), causal inference, experimentation, and ...

Walmart

(USA) Principal, Data Scientist

Cassville, MO · On-site

$110K - $220K/yr

This team leads advancements in generative AI, agentic intelligence, machine learning, measurement, and causal inference to redefine retail experiences, optimize operations, and develop new business ...

Walmart

(USA) Director, Data Science

Noel, MO · On-site

$130K - $260K/yr

Identify opportunities to leverage AI, machine learning, causal inference, optimization, and experimentation to improve pricing decisions. * Drive innovation by evaluating emerging technologies and ...

Walmart

(USA) Director, Data Science

Anderson, MO · On-site

$130K - $260K/yr

Identify opportunities to leverage AI, machine learning, causal inference, optimization, and experimentation to improve pricing decisions. * Drive innovation by evaluating emerging technologies and ...

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Causal Inference Machine Learning Postdoctoral information

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?

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 Missouri? For Causal Inference Machine Learning Postdoctoral jobs in Missouri, the most frequently searched job titles are:
What job categories do people searching Causal Inference Machine Learning Postdoctoral jobs in Missouri look for? The top searched job categories for Causal Inference Machine Learning Postdoctoral jobs in Missouri are:
What cities in Missouri are hiring for Causal Inference Machine Learning Postdoctoral jobs? Cities in Missouri with the most Causal Inference Machine Learning Postdoctoral job openings:
Causal Inference Machine Learning Postdoctoral jobs near you
Infographic showing various Causal Inference Machine Learning Postdoctoral job openings in Missouri as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 21% Part Time, 1% Temporary, and 4% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Machine Learning Engineer, Causal Inference, Level 5

Jobtailor

California, MO • On-site

$150 - $210/hr

Other

Posted 2 days ago

New

Job description

  • Design and build models that quantify causal impact, optimize decision‑making, and drive value for users, advertisers, and the business
  • Develop and productionize causal machine learning solutions (e.g., uplift modeling, heterogeneous treatment effect estimation) using observational and experimental data
  • Design, analyze, and interpret A/B tests and quasi‑experiments; collaborate closely with product and engineering partners to shape experimentation strategies
  • Evaluate technical tradeoffs between model complexity, bias/variance, scalability, and interpretability
  • Conduct code reviews, maintain high engineering standards, and build scalable, maintainable infrastructure
  • Contribute to rapid iteration cycles while ensuring methodological rigor
Requirements
  • Bachelor’s degree in computer science, statistics, economics, or a related technical field, or equivalent practical experience
  • 5+ years of post‑Bachelor’s experience in machine learning, with hands‑on experience in causal inference or experimentation; or Master’s degree in a technical field + 4+ years of post‑grad machine learning experience; or PhD in a relevant technical field + 2 years of post‑grad machine learning experience
  • Demonstrated experience building models to support product decision‑making and policy evaluation through causal techniques
  • Experience designing and analyzing online experiments (A/B tests) and leveraging causal ML in production systems
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