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Phd Causal Inference Jobs in Washington (NOW HIRING)

Senior Data Scientist

Herndon, VA · On-site +1

$160K - $190K/yr

Perform statistical analysis, hypothesis testing, causal inference, and A/B test analysis. * Build ... or PhD preferred * 5+ years of experience building and deploying production ML systems, with a ...

Senior Data Scientist

Herndon, VA · On-site +1

$160K - $190K/yr

Perform statistical analysis, hypothesis testing, causal inference, and A/B test analysis. * Build ... or PhD preferred * 5+ years of experience building and deploying production ML systems, with a ...

Familiarity with experimental design and causal inference methodologies *Familiarity with or ... Recent PhD in relevant field *Expertise in data analysis and machine learning, with experience ...

Principal Data Scientist

Gaithersburg, MD · On-site

$175K - $215K/yr

What We're Looking For Education • Advanced degree (MS or PhD) in a quantitative field -- biology ... Causal inference experience -- a significant differentiator for this role • NLP/LLM expertise ...

... or PhD in data science, machine learning, computer science, statistics, or related highly ... Causal inference / uplift modeling / synthetic controls * Modern ML frameworks: LightGBM/XGBoost ...

... or PhD in data science, machine learning, computer science, statistics, or related highly ... Causal inference / uplift modeling / synthetic controls * Modern ML frameworks: LightGBM/XGBoost ...

Associate Data Scientist

Arlington, VA

$67K - $68K/yr

... or PhD in data science, machine learning, computer science, statistics, or related highly ... Causal inference / uplift modeling / synthetic controls * Modern ML frameworks: LightGBM/XGBoost ...

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Phd Causal Inference information

See Washington salary details

$45.3K

$139.2K

$202.2K

How much do phd causal inference jobs pay per year?

As of Jul 31, 2026, the average yearly pay for phd causal inference in Washington is $139,228.00, according to ZipRecruiter salary data. Most workers in this role earn between $118,900.00 and $156,300.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a PhD Causal Inference researcher, and why are they important?

To thrive as a PhD Causal Inference researcher, you need advanced knowledge of statistics, econometrics, and causal modeling, typically supported by a doctoral degree in a quantitative field. Familiarity with statistical programming languages (such as R or Python), specialized software (like STATA or SAS), and experience with experimental or quasi-experimental methods are essential. Strong analytical thinking, attention to detail, and the ability to communicate complex findings clearly make a candidate stand out. These skills ensure rigorous, credible research that can inform policy, product development, or scientific understanding by accurately identifying causal relationships.

What collaborative opportunities can a PhD specializing in Causal Inference expect within a multidisciplinary research team?

PhD professionals in Causal Inference frequently collaborate with experts from fields such as epidemiology, economics, computer science, and public health. They often work closely with data scientists, subject matter experts, and statisticians to design studies, interpret complex datasets, and develop robust analytical models. This multidisciplinary environment fosters continuous learning and often leads to co-authorship on research publications, participation in grant writing, and involvement in high-impact policy or product decisions. Effective communication and teamwork skills are essential to translate technical findings for diverse audiences and drive actionable insights.

What is a PhD in Causal Inference?

A PhD in Causal Inference is an advanced research degree focused on understanding and identifying cause-and-effect relationships using statistical and computational methods. Students in this field learn to design studies, analyze data, and develop new methodologies to answer complex causal questions in areas such as social sciences, medicine, economics, and artificial intelligence. Graduates often work in academia, research institutions, or industries where evidence-based decision-making is essential.
What are popular job titles related to Phd Causal Inference jobs in Washington? For Phd Causal Inference jobs in Washington, the most frequently searched job titles are:
What cities in Washington are hiring for Phd Causal Inference jobs? Cities in Washington with the most Phd Causal Inference job openings:

2026 PhD Graduate - Statistics and Data Science

The Johns Hopkins University Applied Physics Laboratory

Laurel, MD • On-site

Other

Medical, Dental, Vision, Life, Retirement, PTO

This job post has expired today. Applications are no longer accepted.


Job description

Description

Do you enjoy exploring and analyzing data to find data-driven solution to complex problems?

Do you want to contribute to work that is crucial to maintaining our national security and strength?

Are you continuously searching for new ways to grow your knowledge and improve your skills?

If you are graduating with a PhD in Statistics, Physics, Mathematics, Computer Science, or a related field, we would love to have you join our team! We are seeking a new PhD graduate with expertise in statistics to support multi-disciplinary teams performing a variety of quantitative tasks for defense and national security applications. You will be joining a varied team of engineers, software developers, statisticians, data scientists, and analysts who are committed to advancing the state-of-the-art in performance evaluation of the nation's strategic weapons systems throughout their lifecycle. We believe in continually growing our capabilities and cultivating a work environment that embraces innovation, integrity, trust, and teamwork.

As a member of our team, you will...

  • Work with multi-disciplinary teams to support development of data collection, processing, and analysis efforts to assess the performance of a number of systems supporting the Navy and Air Force.
  • Develop and evaluate statistical models for complex defense applications, including uncertainty quantification, inference, forecasting, and decision support.
  • Apply statistical reasoning for data-driven studies, selecting appropriate methods (e.g., Bayesian or frequentist approaches) based on the problem.
  • Quantify and communicate uncertainty, assumptions, and limitations to support sound decision-making in complex, real-world setting.
  • Use internal funding opportunities to shape the direction of future research.
  • Communicate technical knowledge by articulating ideas clearly through papers and presentations to technical staff, management, and government decision makers.

Qualifications

You meet our minimum qualifications for the job if you...

  • Have a PhD in Data Science, Statistics, Physics, Mathematics, Computer Science or a related field.
  • Demonstrate strong interpersonal skills and the ability to work independently and on a team.
  • Have strong foundations in statistical inference, probability, statistical modeling, and experimental design.
  • Have experience using scientific programming tools such as Python, R, or similar languages for quantitative analysis.
  • Have experience investigating and adapting modern statistical and computational methods to address emerging analysis challenges in sparse, noisy, or high-dimensional data setting.
  • Demonstrate experience with statistical modeling, inference, or experimental design approaches such as Bayesian methods, regression, causal inference, or hypothesis testing...
  • Are able to obtain Interim Secret level security clearance by your start date and can ultimately obtain Top Secret level clearance. If selected, you will be subject to a government security clearance investigation and must meet the requirements for access to classified information. Eligibility requirements include U.S. citizenship.

You will go above and beyond our minimum requirements if you...

  • Have experience in project management or leading technical teams.
  • Have experience in writing technical proposals, particularly to government research projects.
  • Have experience mentoring students, teaching, or communicating complex technical concepts in academic, research, or professional settings.
  • Have contributed to peer-reviewed publications, technical reports, or presentations in statistics, machine learning, applied mathematics, or related fields.
  • Have experience using probabilistic programming frameworks such as Stan, PyMC, or similar tools.
  • Have research or professional experience developing reproducible analytical workflows, computational research tools, or statistical methodologies for complex quantitative problems.

About Us

Why Work at APL?

The Johns Hopkins University Applied Physics Laboratory (APL) brings world-class expertise to our nation's most critical defense, security, space and science challenges. While we are dedicated to solving complex challenges and pioneering new technologies, what makes us truly outstanding is our culture. We offer a vibrant, welcoming atmosphere where you can bring your authentic self to work, continue to grow, and build strong connections with inspiring teammates.

At APL, we celebrate our differences of perspectives and encourage creativity and bold, new ideas. Our employees enjoy generous benefits, including a robust education assistance program, unparalleled retirement contributions, and a healthy work/life balance. APL's campus is located in the Baltimore-Washington metro area. Learn more about our career opportunities athttps://www.jhuapl.edu/careers.

All qualified applicants will receive consideration for employment without regard to race, creed, color, religion, sex, gender identity or expression, sexual orientation, national origin, age, physical or mental disability, genetic information, veteran status, occupation, marital or familial status, political opinion, personal appearance, or any other characteristic protected by applicable law.APL is committed to providing reasonable accommodation to individuals of all abilities, including those with disabilities. If you require a reasonable accommodation to participate in any part of the hiring process, please contactAccessibility@jhuapl.edu.

The referenced pay range is based on JHU APL's good faith belief at the time of posting. Actual compensation may vary based on factors such as geographic location, work experience, market conditions, education/training and skill level with consideration for internal parity. For salaried employees scheduled to work less than 40 hours per week, annual salary will be prorated based on the number of hours worked. APL may offer bonuses or other forms of compensation per internal policy and/or contractual designation. Additional compensation may be provided in the form of a sign-on bonus, relocation benefits, locality allowance or discretionary payments for exceptional performance. APL provides eligible staff with a comprehensive benefits package including retirement plans, paid time off, medical, dental, vision, life insurance, short-term disability, long-term disability, flexible spending accounts, education assistance, and training and development. Applications are accepted on a rolling basis.


Minimum Rate
$105,000 Annually
Maximum Rate
$245,000 Annually