... and machine learning. * Work with JC's diverse data resources, including accreditation survey ... learning methods is welcome, especially when integrated with causal inference approaches and ...
... and machine learning. * Work with JC's diverse data resources, including accreditation survey ... learning methods is welcome, especially when integrated with causal inference approaches and ...
Why this role Evolve's Data Product team builds data and machine-learning products that improve ... causal-inference fundamentals and the ability to contribute to economic or optimization work.
Why this role Evolve's Data Product team builds data and machine-learning products that improve ... causal-inference fundamentals and the ability to contribute to economic or optimization work.
... machine learning, causal inference and scalable intelligence. We partner closely with product ... engineering, policy, and operations teams across Trust to detect and defend against the adversarial ...
... machine learning, causal inference and scalable intelligence. We partner closely with product ... engineering, policy, and operations teams across Trust to detect and defend against the adversarial ...
$200 - $250/hr
The Data Science & Analytics organization accelerates decision-making at scale through analytics, experimentation, causal inference, and machine learning. This role sits within the Audio-Video ...
$200 - $250/hr
The Data Science & Analytics organization accelerates decision-making at scale through analytics, experimentation, causal inference, and machine learning. This role sits within the Audio-Video ...
... machine learning, causal inference and scalable intelligence. We partner closely with product ... engineering, policy, and operations teams across Trust to detect and defend against the adversarial ...
... machine learning, causal inference and scalable intelligence. We partner closely with product ... engineering, policy, and operations teams across Trust to detect and defend against the adversarial ...
$63K - $63K/yr
The postdoc will help with leading in-person and virtual interviews with New England business ... Demonstrated quantitative/econometric skills, ideally including causal inference or panel-data ...
$63K - $63K/yr
The postdoc will help with leading in-person and virtual interviews with New England business ... Demonstrated quantitative/econometric skills, ideally including causal inference or panel-data ...
$150 - $200/hr
... and machine learning solutions to help continually improve these services and accelerate growth ... Additionally, you will apply advanced ML causal inference techniques including synthetic control ...
New
$150 - $200/hr
... and machine learning solutions to help continually improve these services and accelerate growth ... Additionally, you will apply advanced ML causal inference techniques including synthetic control ...
New
$111K - $222K/yr
We're looking for a Senior Machine Learning Engineer to help build and scale the next generation of ... Strong background in one or more of the following: reinforcement learning, causal inference ...
$111K - $222K/yr
We're looking for a Senior Machine Learning Engineer to help build and scale the next generation of ... Strong background in one or more of the following: reinforcement learning, causal inference ...
$65K/yr
Postdoctoral Associate (Faculty) Rutgers, The State University of New Jersey 2026-08-10 ... Experience with place-based research, causal inference, and program evaluationinvolving community ...
$65K/yr
Postdoctoral Associate (Faculty) Rutgers, The State University of New Jersey 2026-08-10 ... Experience with place-based research, causal inference, and program evaluationinvolving community ...
Experience using Python for data analysis, data preparation, and machine learning model development. * Experience with causal inference and experimental design, including statistically rigorous ...
Experience using Python for data analysis, data preparation, and machine learning model development. * Experience with causal inference and experimental design, including statistically rigorous ...
Experience measuring the quality of machine learning or AI systems. * Experience with causal inference methods or Bayesian analysis. * Experience with data warehouses, dbt, or notebook-to-production ...
Experience measuring the quality of machine learning or AI systems. * Experience with causal inference methods or Bayesian analysis. * Experience with data warehouses, dbt, or notebook-to-production ...
... statistical, machine learning and advanced analytical methods as needed. * Design and execute observational and experimental studies of causal inference. * Work with large, complex data sets.
... statistical, machine learning and advanced analytical methods as needed. * Design and execute observational and experimental studies of causal inference. * Work with large, complex data sets.
Advance quantitative methods by integrating causal inference, statistical modeling, and machine learning techniques to solve highly ambiguous and complex measurement challenges. * Drive the creation ...
New
Advance quantitative methods by integrating causal inference, statistical modeling, and machine learning techniques to solve highly ambiguous and complex measurement challenges. * Drive the creation ...
New
$184K - $324K/yr
Sr. Machine Learning Engineer, Foundation Models Inference - Cloud OS & Inference Santa Clara, California, United States Machine Learning and AI We are the Foundation Model Inference team within ...
$184K - $324K/yr
Sr. Machine Learning Engineer, Foundation Models Inference - Cloud OS & Inference Santa Clara, California, United States Machine Learning and AI We are the Foundation Model Inference team within ...
Experience with non-experimental causal inference methods, experimentation and machine learning techniques, ideally in a multi-sided platform setting * Working knowledge of schema design and high ...
Experience with non-experimental causal inference methods, experimentation and machine learning techniques, ideally in a multi-sided platform setting * Working knowledge of schema design and high ...
$79K - $104K/yr
... inference infrastructure that powers our machine learning models. Your work will be instrumental in enhancing the scalability, efficiency, and performance of our AI-driven solutions. You will work ...
$79K - $104K/yr
... inference infrastructure that powers our machine learning models. Your work will be instrumental in enhancing the scalability, efficiency, and performance of our AI-driven solutions. You will work ...
$64K/yr
Postdoctoral Associate for the Center for Climate, Health and Healthcare (CCHH) Recruitment/Posting ... and causal inference methods. * Understanding of HIPAA regulations and/or Human Subjects ...
$64K/yr
Postdoctoral Associate for the Center for Climate, Health and Healthcare (CCHH) Recruitment/Posting ... and causal inference methods. * Understanding of HIPAA regulations and/or Human Subjects ...
$175K - $308K/yr
... Machine Learning and AI Services at Apple help hundreds of millions of customers get the most out ... Apply advanced ML causal inference techniques including synthetic control, metalearning, and ...
$175K - $308K/yr
... Machine Learning and AI Services at Apple help hundreds of millions of customers get the most out ... Apply advanced ML causal inference techniques including synthetic control, metalearning, and ...
$150K - $250K/yr
Lead architecture decisions for training, evaluation, and inference pipelines * Build evaluation ... in machine learning engineering with production ownership * Strong Python skills and deep ...
$150K - $250K/yr
Lead architecture decisions for training, evaluation, and inference pipelines * Build evaluation ... in machine learning engineering with production ownership * Strong Python skills and deep ...
... inference costs against incremental value while maintaining fleet-wide fail-open behaviors ... Deep experience with causal or econometric methods to model the business impact of false positives ...
... inference costs against incremental value while maintaining fleet-wide fail-open behaviors ... Deep experience with causal or econometric methods to model the business impact of false positives ...
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?
| Aspect | Causal Inference Machine Learning Postdoctoral | Data Scientist |
|---|---|---|
| Required Credentials | PhD in statistics, machine learning, or related field | Bachelor's or Master's in data science, computer science, or related field |
| Work Environment | Academic research, research labs, universities | Corporate, tech companies, startups |
| Industry Usage | Research, academia, specialized industry projects | Business analytics, product development, data-driven decision making |
| Common Search/Comparison | Yes | Yes |
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.
Is it difficult to get a causal inference machine learning postdoctoral position?
Securing a causal inference machine learning postdoctoral position can be competitive due to specialized skills required, such as expertise in statistical methods, programming (e.g., Python or R), and a strong research background. Candidates with relevant publications, strong recommendations, and experience in machine learning frameworks often have better chances, but the availability of such positions varies by institution and funding.
What are popular job titles related to Causal Inference Machine Learning Postdoctoral jobs in Kentucky?
For Causal Inference Machine Learning Postdoctoral jobs in Kentucky, the most frequently searched job titles are:
What job categories do people searching Causal Inference Machine Learning Postdoctoral jobs in Kentucky look for?
The top searched job categories for Causal Inference Machine Learning Postdoctoral jobs in Kentucky are:
What cities in Kentucky are hiring for Causal Inference Machine Learning Postdoctoral jobs?
Cities in Kentucky with the most Causal Inference Machine Learning Postdoctoral job openings:
Healthcare Research Scientist
On-site
The Joint Commission
 • Health Care and Social Assistance • 1 - 5K employees1,001 - 5,000 employees
Other
Posted 23 days ago
Key responsibilities
Design and lead applied research studies that estimate associations and causal effects from healthcare data.
Develop and implement advanced analytic methods, including causal inference techniques and machine learning.
Collaborate with internal and external teams to support research dissemination, policy insights, and inform accreditation and quality improvement efforts.
Job description
Overview
#J-18808-LjbffrJoint Commission seeks a Healthcare Research Scientist with deep expertise in causal inference and healthcare data analytics to advance our enterprise-wide research and improvement agenda. The ideal candidate will have demonstrated success in applying rigorous statistical methods to observational data, including electronic health records (EHRs) and administrative claims, to generate actionable insights that support health system improvement, quality improvement strategy, and public accountability. This individual must be adept at managing research partnerships and ensuring that externally communicated findings align with the Joint Commission’s strategic goals and mission. The role involves collaboration across Joint Commissions certification, accreditation, and performance measurement programs and helps extend the organization\'s analytic capabilities in ways that promote quality in healthcare delivery.
Responsibilities- Design and lead applied research studies that estimate associations and causal effects from non-randomized healthcare data, contribute to Joint Commissions priorities in quality measurement, accreditation and certification evaluation, and system-level learning.
- Develop and implement advanced analytic methods, including but not limited to instrumental variables, difference-in-differences, regression discontinuities marginal structural models, propensity score-based techniques, synthetic controls, and machine learning.
- Work with JC’s diverse data resources, including accreditation survey findings and patient level data (PLD) from participating health systems, as well as external sources such as Medicare and Medicaid claims.
- Build relationships and consensus across operational, clinical, and business functions to support the development, execution, and dissemination of research that advances Joint Commission priorities.
- Translate research findings into accessible, policy-relevant insights for diverse audiences including business leaders, regulators, hospitals, and the public.
- Ensure that public-facing research outputs and communication reflect the strategic and reputational interests of the Joint Commission.
- Publish findings in peer-reviewed journals and contribute to internal strategic products, performance improvement resources, and external stakeholder briefings.
- Develop non-technical memos, briefs, and other materials to inform internal leadership decisions and support external stakeholder engagement.
- Collaborate with cross-functional teams within the Joint Commission, the National Quality Forum (NQF), and external partners to inform accreditation standards, quality improvement engagement, benchmarking, and outcomes-driven certification.
- Provide direction to and oversight of data analysts and research assistants assigned to support project work, ensuring high-quality and timely execution of analytic tasks.
- Contribute to a culture of rigor, transparency, and equity in research planning, execution, and dissemination.
Required Qualifications:
- PhD or equivalent in economics, health services research, epidemiology, biostatistics, public policy, or a related quantitative field.
- Doctoral-level experience applying causal inference methods to real-world healthcare data, especially Medicare or Medicaid claims preferred.
- Peer-reviewed publication record in areas such as healthcare economics, outcomes, delivery, policy, quality, or safety.
- Demonstrated success communicating analytic findings and familiarizing non-researchers with research methods.
- Ability to independently code, execute, and troubleshoot statistical analyses in R, Stata, or Python.
- Commitment to Joint Commission’s mission to continuously improve healthcare for the public, in collaboration with key stakeholders.
- Demonstrated track record of designing and overseeing analytic projects from concept through execution, including managing scope, timelines, and outputs in research or applied settings.
Preferred Qualifications:
- Experience with Joint Commission’s quality process and outcome measures in prior work.
- Experience conducting research with or within an organization where outputs must align with institutional mission and communications strategy (e.g., ASPE, CMS, AHRQ, VA, state agencies, consulting companies, etc.).
- Familiarity with predictive modeling or statistical learning methods is welcome, especially when integrated with causal inference approaches and natural language processing (NLP).
- Familiarity with regulatory, payer, or policy contexts (e.g., CMS Conditions of Participation, state Medicaid programs, or alternative payment models).
- Experience working in cross-functional teams, including collaborating across roles and managing project-based responsibilities without direct supervisory authority.
- 2 years post-doctoral experience applying causal inference methods to real-world healthcare data, especially administrative CMS claims.
We offer a comprehensive benefit package. For a complete overview of our benefits package, please visit our Joint Commission Career Page
We are an Equal Opportunity Employer. All qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other status protected by law.
MinUSD $99,000.00/year
MaxUSD $134,000.00/year
About Joint Commission
Sourced by ZipRecruiter
Industry
Health care and social assistance
Company size
1,001 - 5,000 Employees
Headquarters location
Oakbrook Terrace, IL, US
Year founded
1951