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Causal Inference Jobs in New Jersey (NOW HIRING)

(USA) Principal, Data Scientist

Hoboken, NJ · On-site

$132K - $264K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

We are seeking a Principal Data Scientist to solve ambiguous, high-value retail problems through rigorous analytics, ML modeling, experimentation, causal inference, and deployment of scalable ...

Post-Doctoral Associate

Piscataway, NJ · On-site

$63K/yr

  • Medical

  • Dental

  • Life

  • Retirement

  • PTO

Expertise in causal inference and machine learning (in particular reinforcement learning), and strong experience with programming are desired.. Excellent communication and writing skills are needed.s ...

(USA) Principal, Data Scientist

Hoboken, NJ · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Strong experience in machine learning: classification models, regression models, NLP, forecasting, unsupervised models, optimization, graph ML, causal inference, causal ML, statistical learning ...

Hands on experience in causal inference techniques to measure the impact of business decisions. SKILLS: * Experience visualizing and presenting data-driven insights using Power BI and Tableau.

Principal, Data Scientist

Hoboken, NJ · On-site

$110K - $220K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

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

Sr Marketing Data Analyst- Checking & Deposits

Iselin, NJ

$87K - $109K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Marketing Mix Modeling (MMM), attribution, incrementality measurement, or causal inference methodologies. * Customer Lifetime Value (CLV), Net Present Value (NPV), or customer profitability analysis.

(USA) Senior Manager, Advanced Analytics

Hoboken, NJ · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Strong knowledge of experimentation, causal inference, and observational analytical methodologies. * Demonstrated success leading multiple high-impact projects in fast-paced environments with minimal ...

Sr Marketing Data Analyst- Checking & Deposits

Iselin, NJ

$87K - $109K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Marketing Mix Modeling (MMM), attribution, incrementality measurement, or causal inference methodologies. * Customer Lifetime Value (CLV), Net Present Value (NPV), or customer profitability analysis.

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Causal Inference information

See New Jersey salary details

$55.8K

$100.7K

$137.6K

How much do causal inference jobs pay per year?

As of Aug 12, 2026, the average yearly pay for causal inference in New Jersey is $100,743.00, according to ZipRecruiter salary data. Most workers in this role earn between $87,300.00 and $110,200.00 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 New Jersey? The most popular types of Causal Inference jobs in New Jersey are:
What are popular job titles related to Causal Inference jobs in New Jersey? For Causal Inference jobs in New Jersey, the most frequently searched job titles are:
What job categories do people searching Causal Inference jobs in New Jersey look for? The top searched job categories for Causal Inference jobs in New Jersey are:
Infographic showing various Causal Inference job openings in New Jersey as of August 2026, with employment types broken down into 82% Full Time, 16% Part Time, and 2% Contract. Highlights an 70% Physical, 4% Hybrid, and 26% Remote job distribution, with an average salary of $100,743 per year, or $48.4 per hour.

Quantitative Researcher - Public Health, Healthcare Evaluation, & Disability

Mathematica

Princeton, NJ • On-site

Full-time

Posted yesterday

New


Job description

Mathematica is hiring researchers with specific expertise inquantitative research methods, causal inference, and policy research, who willconduct studies and support program evaluation in the areas of public health, healthcare,and disability.
The researchers will support project teams in the planningand execution of rigorous, data-driven research project for clients such as:The Centers for Medicare & Medicaid Services, the Social SecurityAdministration, the Substance Abuse and Mental Health Services Administration,the Agency for Healthcare Research and Quality, the Health Resources &Services Administration the Office of the Assistant Secretary for Planning andEvaluation, leading health foundations, and numerous state and local agenciesand commercial clients.

Responsibilities and expectations:

  • Collaborate with senior staff in a multidisciplinary environment to apply rigorous quantitative research methods, including study design, causal inference, data management, and statistical and econometric analysis for describing or evaluating programs and policies
  • Draft reports, present findings to policy and professional audiences, and publish in professional journals
  • Help develop proposals for new research projects
  • Contribute to the growth, expertise, andinstitutional knowledge of other research staf