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Remote Causal Inference Jobs in Richmond, VA (NOW HIRING)

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How much do remote causal inference jobs pay per hour?

As of Aug 18, 2026, the average hourly pay for remote causal inference in Richmond, VA is $56.22, according to ZipRecruiter salary data. Most workers in this role earn between $46.15 and $66.59 per hour, depending on experience, location, and employer.

What is a remote causal inference?

A Remote Causal Inference job involves using statistical and analytical methods to determine cause-and-effect relationships from data, often for fields like healthcare, social sciences, or business. Professionals in this role work remotely, leveraging tools such as R, Python, or specialized software to analyze experiments, observational studies, or large datasets. Their insights help organizations make data-driven decisions, design better interventions, and accurately measure the impact of policies or treatments. Strong skills in statistics, machine learning, and communication are essential for success in this position.

What are the key skills and qualifications needed to thrive as a remote causal inference specialist?

To thrive as a Remote Causal Inference Specialist, you need strong quantitative and statistical skills, a solid background in econometrics or data science, and typically an advanced degree in a related field. Proficiency with statistical programming languages such as R or Python, experience with causal inference frameworks like propensity score matching or instrumental variables, and familiarity with data visualization tools are crucial. Outstanding problem-solving abilities, clear communication, and self-motivation are essential soft skills for working independently and conveying complex results to non-technical stakeholders. These skills enable accurate, actionable insights from data, which drive evidence-based decision-making in remote, collaborative environments.

How does a remote causal inference specialist typically collaborate with cross-functional teams, and what tools are commonly used?

As a remote Causal Inference specialist, you’ll frequently work with data scientists, product managers, and engineers to design and interpret experiments, analyze observational data, and provide actionable insights. Collaboration usually happens through regular video meetings, shared documentation, and project management tools. Commonly used platforms include Slack or Microsoft Teams for communication, GitHub for code collaboration, and Jupyter Notebooks or RMarkdown for sharing reproducible analyses. These tools help ensure transparency and maintain strong teamwork despite the remote environment.

What are the most commonly searched types of Causal Inference jobs in Richmond, VA?

The most popular types of Causal Inference jobs in Richmond, VA are:

What are popular job titles related to Remote Causal Inference jobs in Richmond, VA?

For Remote Causal Inference jobs in Richmond, VA, the most frequently searched job titles are:

What job categories do people searching Remote Causal Inference jobs in Richmond, VA look for?

The top searched job categories for Remote Causal Inference jobs in Richmond, VA are:

What cities near Richmond, VA are hiring for Remote Causal Inference jobs?

Cities near Richmond, VA with the most Remote Causal Inference job openings:

Remote Causal Inference jobs near you
Infographic showing various Remote Causal Inference job openings in Richmond, VA as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% Remote job distribution, with an average salary of $116,945 per year, or $56.2 per hour.

Director of Data Science, Credit Risk

Mission Lane

Richmond, VA • On-site, Remote

$185K - $219K/yr

Full-time

Re-posted yesterday

Job description

Mission Lane is combining the power of data, technology, and exceptional service to pave a clear way forward for millions of people on the path to financial success. By attracting top talent and leveraging cutting-edge technology, we're enabling people to unlock real financial progress. Sound like a mission you can get behind?

About the Role

As a Director of Data Science, Credit Risk, you will lead a data science team and cross-functional projects to innovate and improve the machine learning models we rely on to make billions of dollars of efficient and accurate decisions and to enable financial progress for our customers.

As a Director of Data Science, you'll:

Lead the design, development, and deployment of machine learning models to solve practical problems and help our business and customers reach their financial goals. You'll partner with business leaders and technical experts across the company to develop new data sources, improve our modeling methodology, and apply models with sound risk management.

You are a person who:

  • Has a PhD in a quantitative field and 5+ years of experience in a related leadership role
  • Has a BS / MS in a quantitative field and 8+ years of experience in a related leadership role
  • Has experience applying data science to credit risk management and is excited to build on a multi-billion-dollar portfolio that's growing every day.
  • Can make your team better every day because you can be clear about goals and the team's purpose. You can execute through education, organization, and trust.
  • Can grow members of your team because you can help them identify their strengths and weaknesses, put them in a position to succeed, and get them the training and opportunities they need.
  • Has a deep understanding of the field of data science and can communicate a vision to your team on how the field can be applied to solve difficult, practical problems.
  • Has created, deployed, and managed experiments and models in production systems. You can genuinely speak to practitioners about the fundamental principles and challenges required to be successful in applied work.
  • Practices solid fundamentals with software engineering (test-driven development, code review, refactoring) and the PyData stack (numpy, scikit-learn, pandas, etc.).

You get bonus points for:

  • Experience solving problems in consumer lending or fintech
  • Interest in advancing the frontiers of credit underwriting through the creation of new data sources, causal inference, and neural networks

We're offering:

We're committed to ensuring our team members have balance in their lives. Our comprehensive benefits package provides the support you need to thrive at work and at home.

  • Work: An engaging culture with access to training programs and advancement opportunities
  • Life: Full health, dental, and vision benefits, Flexible Spending Account (for medical and childcare expenses), paid parental leave, and a 401k Company Match
  • Balance: Generous PTO, flexible schedules, a Calm App subscription, and more

Compensation:
Annual full-time starting base salary range: $185,000 - $219,000

This role is eligible for additional compensation in the forms of participation in our annual incentive and equity programs.

Pay is based on factors such as work experience, education, certification(s), training, skills, and competencies related to the role. Mission Lane also offers a comprehensive benefits plan, which includes paid time off, 401(k) match, a monthly wellness stipend, health/ dental/ vision insurance options, disability coverage, paid parental leave, flexible spending account (for childcare and healthcare), life insurance, and a remote-friendly work environment.

About Mission Lane:

Founded in December 2018, Mission Lane is a purpose-driven fintech company based in the U.S., with headquarters in Richmond, Virginia.

It all started with a realization: nearly fifty percent of the adult population in the U.S. doesn't have access to a clear line of credit. Most traditional credit card companies either overlook or overcharge this group because they have less-than-perfect credit scores or no scores at all. We decided this just wouldn't do.

In partnership with our sponsor banks, we offer credit cards under the Mission Lane brand name, with better, clearer terms, and a more refined customer experience than the alternatives available to people working hard to improve their credit. To date, over four million consumers have chosen Mission Lane, earning high customer ratings on Credit Karma for its market segment and industry leading Net Promoter scores.

Mission Lane has cumulatively raised over $600 million of equity from leading investors, including Invus Opportunities, QED Investors, LL Funds, funds affiliated with Oaktree Capital Management, and other leading investors.

Our commitment to a workplace built on respect and dignity is guided by our core value of Unity. We believe that everyone plays a vital role in our shared purpose, and we actively cultivate an environment where all individuals have the opportunity to do their best work. By fostering a culture of empathy and collaboration, we create a strong sense of belonging and support for every team member.

Mission Lane is an equal opportunity employer. We do not discriminate on the basis of race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, or any other protected status.

Mission Lane provides reasonable accommodations to applicants who need them for medical or religious reasons, as required by law. Applicants can initiate an accommodation request by contacting peopleexperience@missionlane.com.

Mission Lane is not sponsoring new applicant employment authorization and please, no third-party recruiters.

Application Integrity:

Our cardholders trust us with their financial well-being, and this trust starts with the integrity of the people on our team. We're looking for team members who share our dedication to transparency and truth. Please verify that the information in your application is accurate and complete.

Providing any information to Mission Lane that is not completely truthful at any point during the application or hiring process may result in removal from the hiring process, disqualification from future opportunities, withdrawal of an offer or other sanctions for candidates and, in addition for employees, disciplinary action, up to and including termination of employment.