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Phd Causal Inference Jobs in Virginia (NOW HIRING)

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 ...

... 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 Virginia salary details

$39.7K

$121.9K

$177K

How much do phd causal inference jobs pay per year?

As of Jun 10, 2026, the average yearly pay for phd causal inference in Virginia is $121,874.00, according to ZipRecruiter salary data. Most workers in this role earn between $104,100.00 and $136,800.00 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 Virginia? For Phd Causal Inference jobs in Virginia, the most frequently searched job titles are:
What cities in Virginia are hiring for Phd Causal Inference jobs? Cities in Virginia with the most Phd Causal Inference job openings:
Senior Manager, Data Scientist -Retail Bank Data Science Experimentation Lead

Senior Manager, Data Scientist -Retail Bank Data Science Experimentation Lead

Capital One

Mclean, VA • On-site

Full-time

Posted 22 days ago


Capital One rating

7.7

Company rating: 7.7 out of 10

Based on 134 frontline employees who took The Breakroom Quiz

72nd of 141 rated banks


Job description

Senior Manager, Data Scientist -Retail Bank Data Science Experimentation Lead

Data is at the center of everything we do. As a startup, we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision-making.

As a Data Scientist at Capital One, you'll be part of a team that's leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.

Team Description

The Retail Bank Data Science is establishing a centralized authority for experimental design to validate and prioritize competing hypotheses. As the DoE and Causal Inference Lead, you will act as a strategic force multiplier, ensuring that our product roadmap is validated through rigorous testing and providing a clear, defensible line of sight into the incremental value of our initiatives. You will lead the "Design of Experiments" center of excellence, bridging the gap between technical data science and business-line execution.

Role Description

In this role, you will:

  • Standardize how we measure incrementality across the organization to ensure metric improvements are tied to specific, isolated initiatives, reducing misattribution.

  • Upstream Product Prioritization: Work with Product Managers and Business Analysts to design in-market tests early in the lifecycle, validating high-risk assumptions before full-scale development.

  • Establish Experimental Infrastructure: Build the infrastructure for testing, including a centralized repository for hypotheses, known covariates, causal models, and results.

  • Mentorship & Consultation: Consult with Data Scientists and Analysts on advanced causal inference techniques for observational data where A/B testing isn't feasible.

  • Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver a product customers love.


The Ideal Candidate is:

  • Strategic Impact & Experimental Rigor. Proven track record of driving strategic business value by optimizing customer experience funnels and risk policies, effectively evaluating external data, and institutionalizing closed-loop experimental frameworks to align predictive backtesting with live operational outcomes.

  • Customer first. You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it's about making the right decision for our customers.

  • A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You're passionate about talent development for your own team and beyond.

  • Technical. You're comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing data science solutions using open-source tools and cloud computing platforms.

Basic Qualifications:

  • Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date:

    • A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 7 years of experience performing data analytics

    • A Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration plus 5 years of experience performing data analytics

    • A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 2 years of experience performing data analytics

  • At least 2 years of experience leveraging open source programming languages for large scale data analysis

  • At least 2 years of experience working with machine learning

  • At least 2 years of experience utilizing relational databases

Preferred Qualifications:

  • PhD in "STEM" field (Science, Technology, Engineering, or Mathematics) plus 4 years of experience in data analytics

  • At least 1 year of experience working with AWS

  • At least 1 year of experience managing people

  • At least 5 years' experience in Python, Scala, or R for large scale data analysis

  • At least 5 years' experience with machine learning

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.

McLean, VA: $229,900 - $262,400 for Sr Mgr, Data Science











Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter.

This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.

Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at theCapital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.

This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.

If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.

For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com

Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.

Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).


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