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Causal Inference Machine Learning Postdoctoral Jobs in Missouri

Walmart

Principal, 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

Principal, 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

Principal, 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 ...

Enterprise Holdings

Data Scientist

Saint Louis, MO · On-site

Apply causal inference techniques using observational data to uncover relationships * Prepare and ... deep learning * Must have experience using libraries like tensorflow or pytorch * Must have ...

Enterprise Holdings

Data Scientist

Saint Louis, MO · On-site

$85 - $115/hr

Apply causal inference techniques using observational data to uncover relationships * Prepare and ... deep learning * Must have experience using libraries like tensorflow or pytorch * Must have ...

Enterprise Holdings

Data Scientist

Saint Louis, MO · On-site

Apply causal inference techniques using observational data to uncover relationships * Prepare and ... deep learning * Must have experience using libraries like tensorflow or pytorch * Must have ...

Socket.dev

Data Scientist

California, MO · On-site

$120 - $180/hr

Apply causal inference techniques (e.g., difference-in-differences, propensity score matching ... Experience with reinforcement learning or bandit algorithms for dynamic experimentation.

Washington University of St. Louis

Biomarker identification through the use of machine learning and AI approaches. * Integration of ... causal and druggable targets. Working Conditions: This position will be located at Dr. Cruchaga ...

Enterprise Holdings

Data Scientist

Saint Louis, MO · Remote

Apply causal inference techniques using observational data to uncover relationships * Prepare and ... deep learning * Must have experience using libraries like tensorflow or pytorch * Must have ...

Walmart

Principal, Data Scientist

Cassville, MO · On-site

$110K - $220K/yr

Strong expertise in statistical modeling, machine learning, experimentation, causal inference, and data science methodologies. * Experience building and deploying scalable machine learning solutions ...

Walmart

Principal, Data Scientist

Anderson, MO · On-site

$110K - $220K/yr

Strong expertise in statistical modeling, machine learning, experimentation, causal inference, and data science methodologies. * Experience building and deploying scalable machine learning solutions ...

Walmart

Principal, Data Scientist

Noel, MO · On-site

$110K - $220K/yr

Strong expertise in statistical modeling, machine learning, experimentation, causal inference, and data science methodologies. * Experience building and deploying scalable machine learning solutions ...

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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.

Senior Product Manager - Data and AI Platform

ServiceTitan, Inc.

California, MO • On-site

$137.90 - $221.40/hr

Other

Medical, Dental, Vision, Retirement

Posted 7 days ago

Job description

About the Role

ServiceTitan is building the operating system for the trades and is looking for a Staff Product Manager to join our Data & AI Platform team. The role focuses on leading algorithmic systems such as ranking, deduplication, and causal inference that underpin many downstream product features. It is a senior individual‑contributor position that requires deep statistical thinking and the ability to translate ambiguous, data‑driven problems into clear, actionable product requirements.

What you’ll do
  • Define and own the roadmap for algorithmic systems that are highest priority based on domain team and customer needs (ranking, deduplication, causal inference, or similar).
  • Translate customer pain points—such as bad matches, untrustworthy rankings, and misleading conclusions—into statistically rigorous product requirements.
  • Co‑author PRDs for problems where the “right answer” is not obvious, defining evaluation criteria as part of the solution.
  • Partner with ML and engineering teams to evaluate model tradeoffs (precision/recall, false‑positive cost, explainability vs. accuracy) and make product decisions when no clean answer exists.
  • Set measurable, multi‑quarter goals for algorithmic system health and lead cross‑functional teams toward them with rigor.
  • Lead discovery with domain product teams and customers to understand where algorithmic errors impact time, money, or trust.
  • Proactively resolve disagreements over methodology, ownership, and model quality before they stall other teams.
What you’ll bring
  • 5+ years of product management experience in enterprise B2B SaaS with a strong track record.
  • Experience with ranking/recommendation systems, entity resolution, or causal inference—ideally across multiple domains.
  • Genuine statistical fluency, comfortable with precision/recall tradeoffs, confounding vs. causation, and model evaluation.
  • Demonstrated ability to define evaluation criteria and “what correct looks like” for new statistical problems from scratch.
  • Comfort with context‑switching between algorithmic domains as priorities shift.
  • Strong communication skills, able to explain model tradeoffs to domain PMs, ML engineers, and customers at varying levels of technical detail.
  • Self‑starter who takes initiative and holds themselves accountable to outcomes; “mostly works” is not good enough.
Why This Role Matters

Algorithmic systems such as ranking, deduplication, and causal inference quietly decide what ServiceTitan surfaces, trusts, and acts on for both internal teams and customers. A wrong decision can lead to a customer trusting a bad recommendation or duplicate records remaining separate, which may go unnoticed. Your work will apply statistical rigor to decisions that are rarely handled by PMs, ensuring the systems on which many teams depend are accurate and trustworthy.

Benefits
  • Flex time, recognition, and support for autonomous work.
  • Comprehensive onboarding, leadership training, and continuous learning opportunities.
  • Holistic health and wellness benefits: company‑paid medical, dental, and vision; FSA and HSA; 401k match; telehealth and wellness programs.
  • Parental leave and reproductive health support; pet insurance; legal advisory services; financial planning tools.
Compensation

For United States candidates, the base salary range for this role is $147,600 - $221,400 (Zone1: CA, CT, DC, MD, MA, NJ, NY, VA, WA) or $137,900 - $206,900 (Zone2: other US locations). Compensation is based on experience, skill set, and performance and may include an annual bonus, equity, and other benefits.

ServiceTitan is committed to fair and equitable compensation for all employees. We comply with all applicable minimum wage laws.

EEO Statement

ServiceTitan is an equal opportunity employer and does not discriminate against employees or applicants on the basis of race, color, religion, sex, national origin, age, disability, pregnancy, genetic information, veteran status, or any other protected characteristic.

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