Data Scientist
Pittsburgh, PA · On-site
Recommendation systems, Time-series forecasting (Prophet, NeuralProphet, Chronos, Lag-Llama, etc.), NLP / LLMs (fine-tuning, RAG, evaluation, prompt engineering), Causal inference / uplift modeling ...
Data Scientist
Pittsburgh, PA · On-site
Recommendation systems, Time-series forecasting (Prophet, NeuralProphet, Chronos, Lag-Llama, etc.), NLP / LLMs (fine-tuning, RAG, evaluation, prompt engineering), Causal inference / uplift modeling ...
... causal inference, and subgroup inference. * Integrate policy analysis into evidence generation: identify policy levers (e.g., Medicaid policy, payer coverage, reimbursement pathways) and translate ...
... causal inference, and subgroup inference. * Integrate policy analysis into evidence generation: identify policy levers (e.g., Medicaid policy, payer coverage, reimbursement pathways) and translate ...
... causal inference, and subgroup inference. * Integrate policy analysis into evidence generation: identify policy levers (e.g., Medicaid policy, payer coverage, reimbursement pathways) and translate ...
... causal inference, and subgroup inference. * Integrate policy analysis into evidence generation: identify policy levers (e.g., Medicaid policy, payer coverage, reimbursement pathways) and translate ...
Candidates with experience and/or an interest in cancer clinical trials, pediatric research, the interface between biostatistics and artificial intelligence, and causal inference are especially ...
Candidates with experience and/or an interest in cancer clinical trials, pediatric research, the interface between biostatistics and artificial intelligence, and causal inference are especially ...
Associate Data Scientist
Pittsburgh, PA · On-site
$57K - $57K/yr
Causal inference / uplift modeling / synthetic controls * Modern ML frameworks: LightGBM/XGBoost, CatBoost, PyTorch,JAX, TensorFlow) * LLMs / agentic workflows (LangChain/LlamaIndex/Haystack)
Associate Data Scientist
Pittsburgh, PA · On-site
$57K - $57K/yr
Causal inference / uplift modeling / synthetic controls * Modern ML frameworks: LightGBM/XGBoost, CatBoost, PyTorch,JAX, TensorFlow) * LLMs / agentic workflows (LangChain/LlamaIndex/Haystack)
Conduct causal inference studies and exploratory analyses to measure the impact of strategic initiatives and inform decision-making at scale. * Collaborate within data science and analytics ...
Conduct causal inference studies and exploratory analyses to measure the impact of strategic initiatives and inform decision-making at scale. * Collaborate within data science and analytics ...
Senior Data Scientist
Pittsburgh, PA · On-site
Causal inference / uplift modeling / synthetic controls * Modern ML frameworks: LightGBM/XGBoost, CatBoost, PyTorch,JAX, TensorFlow) * LLMs / agentic workflows (LangChain/LlamaIndex/Haystack)
Senior Data Scientist
Pittsburgh, PA · On-site
Causal inference / uplift modeling / synthetic controls * Modern ML frameworks: LightGBM/XGBoost, CatBoost, PyTorch,JAX, TensorFlow) * LLMs / agentic workflows (LangChain/LlamaIndex/Haystack)
Causal inference / uplift modeling / synthetic controls * Modern ML frameworks: LightGBM/XGBoost, CatBoost, PyTorch,JAX, TensorFlow) * LLMs / agentic workflows (LangChain/LlamaIndex/Haystack)
Causal inference / uplift modeling / synthetic controls * Modern ML frameworks: LightGBM/XGBoost, CatBoost, PyTorch,JAX, TensorFlow) * LLMs / agentic workflows (LangChain/LlamaIndex/Haystack)
Data Scientist
Pittsburgh, PA · On-site
Causal inference / uplift modeling / synthetic controls * Modern ML frameworks: LightGBM/XGBoost, CatBoost, PyTorch,JAX, TensorFlow) * LLMs / agentic workflows (LangChain/LlamaIndex/Haystack)
Data Scientist
Pittsburgh, PA · On-site
Causal inference / uplift modeling / synthetic controls * Modern ML frameworks: LightGBM/XGBoost, CatBoost, PyTorch,JAX, TensorFlow) * LLMs / agentic workflows (LangChain/LlamaIndex/Haystack)
Associate Data Scientist
Pittsburgh, PA · On-site
$57K - $57K/yr
Causal inference / uplift modeling / synthetic controls * Modern ML frameworks: LightGBM/XGBoost, CatBoost, PyTorch,JAX, TensorFlow) * LLMs / agentic workflows (LangChain/LlamaIndex/Haystack)
Associate Data Scientist
Pittsburgh, PA · On-site
$57K - $57K/yr
Causal inference / uplift modeling / synthetic controls * Modern ML frameworks: LightGBM/XGBoost, CatBoost, PyTorch,JAX, TensorFlow) * LLMs / agentic workflows (LangChain/LlamaIndex/Haystack)
Associate Data Scientist with Security Clearance
Pittsburgh, PA · On-site
$57K - $57K/yr
Causal inference / uplift modeling / synthetic controls * Modern ML frameworks: LightGBM/XGBoost, CatBoost, PyTorch,JAX, TensorFlow) * LLMs / agentic workflows (LangChain/LlamaIndex/Haystack)
Associate Data Scientist with Security Clearance
Pittsburgh, PA · On-site
$57K - $57K/yr
Causal inference / uplift modeling / synthetic controls * Modern ML frameworks: LightGBM/XGBoost, CatBoost, PyTorch,JAX, TensorFlow) * LLMs / agentic workflows (LangChain/LlamaIndex/Haystack)
Data Scientist
Pittsburgh, PA · On-site
Causal inference / uplift modeling / synthetic controls * Modern ML frameworks: LightGBM/XGBoost, CatBoost, PyTorch,JAX, TensorFlow) * LLMs / agentic workflows (LangChain/LlamaIndex/Haystack)
Data Scientist
Pittsburgh, PA · On-site
Causal inference / uplift modeling / synthetic controls * Modern ML frameworks: LightGBM/XGBoost, CatBoost, PyTorch,JAX, TensorFlow) * LLMs / agentic workflows (LangChain/LlamaIndex/Haystack)
Causal inference / uplift modeling / synthetic controls * Modern ML frameworks: LightGBM/XGBoost, CatBoost, PyTorch,JAX, TensorFlow) * LLMs / agentic workflows (LangChain/LlamaIndex/Haystack)
Causal inference / uplift modeling / synthetic controls * Modern ML frameworks: LightGBM/XGBoost, CatBoost, PyTorch,JAX, TensorFlow) * LLMs / agentic workflows (LangChain/LlamaIndex/Haystack)
Data Scientist
Pittsburgh, PA · On-site
Causal inference / uplift modeling / synthetic controls * Modern ML frameworks: LightGBM/XGBoost, CatBoost, PyTorch,JAX, TensorFlow) * LLMs / agentic workflows (LangChain/LlamaIndex/Haystack)
Data Scientist
Pittsburgh, PA · On-site
Causal inference / uplift modeling / synthetic controls * Modern ML frameworks: LightGBM/XGBoost, CatBoost, PyTorch,JAX, TensorFlow) * LLMs / agentic workflows (LangChain/LlamaIndex/Haystack)
Conduct causal inference studies and exploratory analyses to measure the impact of strategic initiatives and inform decision-making at scale. * Collaborate within data science and analytics ...
Conduct causal inference studies and exploratory analyses to measure the impact of strategic initiatives and inform decision-making at scale. * Collaborate within data science and analytics ...
Associate Data Scientist
Pittsburgh, PA · On-site
$55K - $55K/yr
Causal inference / uplift modeling / synthetic controls * Modern ML frameworks: LightGBM/XGBoost, CatBoost, PyTorch,JAX, TensorFlow) * LLMs / agentic workflows (LangChain/LlamaIndex/Haystack)
Associate Data Scientist
Pittsburgh, PA · On-site
$55K - $55K/yr
Causal inference / uplift modeling / synthetic controls * Modern ML frameworks: LightGBM/XGBoost, CatBoost, PyTorch,JAX, TensorFlow) * LLMs / agentic workflows (LangChain/LlamaIndex/Haystack)
Conduct causal inference studies and exploratory analyses to measure the impact of strategic initiatives and inform decision-making at scale. * Collaborate within data science and analytics ...
Conduct causal inference studies and exploratory analyses to measure the impact of strategic initiatives and inform decision-making at scale. * Collaborate within data science and analytics ...
Postdoctoral Scholar
University Park, PA · On-site
... causal inference, synthetic data, reproducibility, intersection of AI and data privacy, and work with survey, census, health/genomic and other complex data. The scholar will have an opportunity to ...
Postdoctoral Scholar
University Park, PA · On-site
... causal inference, synthetic data, reproducibility, intersection of AI and data privacy, and work with survey, census, health/genomic and other complex data. The scholar will have an opportunity to ...
... and causal inference. * Experience working with high-dimensional, large-scale molecular and cellular datasets (e.g., genomic, transcriptomic, epigenomic, proteomic, metabolomic/lipidomic, imaging ...
... and causal inference. * Experience working with high-dimensional, large-scale molecular and cellular datasets (e.g., genomic, transcriptomic, epigenomic, proteomic, metabolomic/lipidomic, imaging ...
Senior Data Scientist
Pittsburgh, PA · On-site
Causal inference / uplift modeling / synthetic controls * Modern ML frameworks: LightGBM/XGBoost, CatBoost, PyTorch,JAX, TensorFlow) * LLMs / agentic workflows (LangChain/LlamaIndex/Haystack)
Senior Data Scientist
Pittsburgh, PA · On-site
Causal inference / uplift modeling / synthetic controls * Modern ML frameworks: LightGBM/XGBoost, CatBoost, PyTorch,JAX, TensorFlow) * LLMs / agentic workflows (LangChain/LlamaIndex/Haystack)
Causal Inference information
See Pennsylvania salary details
$55.1K - $62.5K
0% of jobs
$62.5K - $69.8K
1% of jobs
$69.8K - $77.1K
3% of jobs
$77.1K - $84.5K
17% of jobs
$86K is the 25th percentile. Wages below this are outliers.
$84.5K - $91.8K
18% of jobs
The median wage is $96.4K / yr.
$91.8K - $99.1K
17% of jobs
$99.1K - $106.5K
18% of jobs
$106.7K is the 75th percentile. Wages above this are outliers.
$106.5K - $113.8K
17% of jobs
$113.8K - $121.2K
6% of jobs
$121.2K - $128.5K
1% of jobs
$128.5K - $135.8K
1% of jobs
$55.1K
$99.5K
$135.8K
How much do causal inference jobs pay per year?
As of Aug 11, 2026, the average yearly pay for causal inference in Pennsylvania is $99,469.00, according to ZipRecruiter salary data. Most workers in this role earn between $86,200.00 and $108,800.00 per year, depending on experience, location, and employer.
Is causal inference still relevant?
Causal inference is a vital skill for data analysts and researchers, as it helps determine cause-and-effect relationships in data. It remains highly relevant across industries such as healthcare, economics, and technology, especially with the increasing availability of large datasets and advanced statistical tools like R and Python. Professionals in this field are in demand for designing experiments, analyzing observational data, and informing decision-making processes.
What skills and qualifications are needed for a causal inference position?
Success in a Causal Inference role requires strong statistical knowledge, expertise in experimental and quasi-experimental methodologies, and advanced proficiency in programming languages like R or Python, typically acquired with an advanced degree in statistics, economics, data science, or a related field. Familiarity with specialized statistical software (such as Stata, SAS, or causal inference packages in R/Python), as well as experience with large datasets and machine learning tools, is highly valued. Excellent problem-solving abilities, clear communication, and collaboration skills are essential soft skills for effectively conveying complex findings to diverse teams. These competencies are critical to producing reliable insights that guide evidence-based decision-making in business, healthcare, or policy settings.
What jobs use causal inference?
Causal inference is used in various roles such as data scientist, epidemiologist, econometrician, and policy analyst. These jobs involve analyzing data to determine cause-and-effect relationships, often using statistical tools and programming languages like R or Python. Professionals in these fields work in industries like healthcare, finance, government, and technology to inform decision-making and policy development.
What are common challenges faced in a causal inference position?
Professionals in Causal Inference often encounter challenges such as dealing with confounding factors, addressing selection bias, and ensuring the validity of assumptions behind statistical models. They must carefully design experiments or leverage observational data while staying vigilant about potential data quality issues and model limitations. Collaboration with subject matter experts, data engineers, and business stakeholders is common to ensure accurate contextualization of results. Overcoming these challenges requires a mix of technical acumen and strong communication skills to translate complex analyses into actionable recommendations.
What is a causal inference?
A Causal Inference job involves using statistical and computational methods to determine cause-and-effect relationships from data. Professionals in this field work with observational and experimental data to identify causal impacts, often in domains like economics, healthcare, social sciences, and technology. They apply techniques such as propensity score matching, instrumental variables, and difference-in-differences to ensure rigorous analysis. These roles are commonly found in academia, policy research, and data science teams within tech and finance companies. Strong skills in statistics, programming (e.g., Python, R), and experimental design are typically required.
What are the most commonly searched types of Causal Inference jobs in Pennsylvania? The most popular types of Causal Inference jobs in Pennsylvania are:
What are popular job titles related to Causal Inference jobs in Pennsylvania? For Causal Inference jobs in Pennsylvania, the most frequently searched job titles are:
What job categories do people searching Causal Inference jobs in Pennsylvania look for? The top searched job categories for Causal Inference jobs in Pennsylvania are:
What cities in Pennsylvania are hiring for Causal Inference jobs? Cities in Pennsylvania with the most Causal Inference job openings:
Carnegie Mellon University rating
8.6
Based on 24 frontline employees who took The Breakroom Quiz
67th of 617 rated colleges and universities
Job description
Job Summary:
Carnegie Mellon University is a leading institution focused on innovation and research. They are seeking a Data Scientist to leverage advanced statistics, data analytics, machine learning, and artificial intelligence to address cybersecurity challenges for government and industry clients.
Responsibilities:
• Work with customers to identify areas where advanced statistical techniques can help tackle problems, plan and develop prototype solutions, and build out final products.
• Co-author research proposals, execute studies, and present findings to DoW sponsors and at academic conferences.
• Work on a wide range of projects including research in generative AI and large language models, computer vision, multimodal AI, agentic AI, and assurance of AI systems.
• Craft metrics and experimental designs for large-scale cybersecurity research programs, develop human-in-the-loop machine learning solutions, and build classifiers to identify security vulnerabilities.
Qualifications:
Required:
• BS in data science, machine learning, computer science, statistics, or related highly-quantitative discipline with eight (8) years of experience or equivalent combination of training or experience; or MS in data science, machine learning, computer science, statistics, or related highly-quantitative discipline with five (5) years of experience; or PhD in data science, machine learning, computer science, statistics, or related highly-quantitative discipline with two (2) years of experience.
• Willingness to complete modest travel to various locations to support the SEI’s overall mission.
• You will be subject to a background check and must be able obtain and maintain a U.S. Department of War security clearance.
• Experience in predictive modeling, data science, and/or AI & machine learning
• Deep understanding of statistical modeling techniques and advanced data analytics
• Proficient with at least one mathematical/statistical programming package (e.g., R, python numpy/scipy/pandas/polars, MATLAB, etc.)
• Innovative and inquisitive with ability to imagine novel analytical solutions to problems Thrives in a multi-disciplinary environment
• Strong communication skills
• Expertise in one or more of the following: Recommendation systems, Time-series forecasting (Prophet, NeuralProphet, Chronos, Lag-Llama, etc.), NLP / LLMs (fine-tuning, RAG, evaluation, prompt engineering), Causal inference / uplift modeling / synthetic controls, Modern ML frameworks: LightGBM/XGBoost, CatBoost, PyTorch,JAX, TensorFlow), LLMs / agentic workflows (LangChain/LlamaIndex/Haystack), Experience deploying models (FastAPI, Triton, KServe, SageMaker, Vertex AI, or similar), Experience working with big data (Spark, Trino, Snowflake, BigQuery, Databricks)
Preferred:
• Experience in cybersecurity and privacy is a plus
• Experience in U.S. Government work and/or with FFRDCs, UARCs an National Labs is a plus
• Demonstrated ability to learn new concepts and grow into new areas of work
Company:
Carnegie Mellon University is a research university offering programs and research across engineering, science, arts, and business. Founded in 1900, the company is headquartered in Pittsburgh, USA, with a team of 5001-10000 employees. The company is currently Late Stage.
Carnegie Mellon University is a leading institution focused on innovation and research. They are seeking a Data Scientist to leverage advanced statistics, data analytics, machine learning, and artificial intelligence to address cybersecurity challenges for government and industry clients.
Responsibilities:
• Work with customers to identify areas where advanced statistical techniques can help tackle problems, plan and develop prototype solutions, and build out final products.
• Co-author research proposals, execute studies, and present findings to DoW sponsors and at academic conferences.
• Work on a wide range of projects including research in generative AI and large language models, computer vision, multimodal AI, agentic AI, and assurance of AI systems.
• Craft metrics and experimental designs for large-scale cybersecurity research programs, develop human-in-the-loop machine learning solutions, and build classifiers to identify security vulnerabilities.
Qualifications:
Required:
• BS in data science, machine learning, computer science, statistics, or related highly-quantitative discipline with eight (8) years of experience or equivalent combination of training or experience; or MS in data science, machine learning, computer science, statistics, or related highly-quantitative discipline with five (5) years of experience; or PhD in data science, machine learning, computer science, statistics, or related highly-quantitative discipline with two (2) years of experience.
• Willingness to complete modest travel to various locations to support the SEI’s overall mission.
• You will be subject to a background check and must be able obtain and maintain a U.S. Department of War security clearance.
• Experience in predictive modeling, data science, and/or AI & machine learning
• Deep understanding of statistical modeling techniques and advanced data analytics
• Proficient with at least one mathematical/statistical programming package (e.g., R, python numpy/scipy/pandas/polars, MATLAB, etc.)
• Innovative and inquisitive with ability to imagine novel analytical solutions to problems Thrives in a multi-disciplinary environment
• Strong communication skills
• Expertise in one or more of the following: Recommendation systems, Time-series forecasting (Prophet, NeuralProphet, Chronos, Lag-Llama, etc.), NLP / LLMs (fine-tuning, RAG, evaluation, prompt engineering), Causal inference / uplift modeling / synthetic controls, Modern ML frameworks: LightGBM/XGBoost, CatBoost, PyTorch,JAX, TensorFlow), LLMs / agentic workflows (LangChain/LlamaIndex/Haystack), Experience deploying models (FastAPI, Triton, KServe, SageMaker, Vertex AI, or similar), Experience working with big data (Spark, Trino, Snowflake, BigQuery, Databricks)
Preferred:
• Experience in cybersecurity and privacy is a plus
• Experience in U.S. Government work and/or with FFRDCs, UARCs an National Labs is a plus
• Demonstrated ability to learn new concepts and grow into new areas of work
Company:
Carnegie Mellon University is a research university offering programs and research across engineering, science, arts, and business. Founded in 1900, the company is headquartered in Pittsburgh, USA, with a team of 5001-10000 employees. The company is currently Late Stage.
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