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Phd Causal Inference Jobs in Virginia (NOW HIRING)

Team Velocity

Senior Data Scientist

Herndon, VA · On-site +1

$160K - $220K/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 ...

Team Velocity

Senior Data Scientist

Herndon, VA · On-site +1

$160K - $220K/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 ...

Cmu

Associate Data Scientist

Arlington, VA · On-site

$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 ...

Cmu

Data Scientist

Arlington, VA · On-site

... 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

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$39.7K

$121.9K

$177K

How much do phd causal inference jobs pay per year?

As of Jul 13, 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:
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Phd Causal Inference jobs near you
Senior Data Scientist

Senior Data Scientist

Team Velocity

Herndon, VA • On-site, Remote

$160K - $220K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 15 days ago

Job description

We are seeking a Senior Data Scientist to develop machine learning models, predictive analytics, and AI-driven solutions that improve customer engagement, marketing performance, operational efficiency, and business intelligence. The role partners with Product, Data Engineering, Software Engineering, Analytics, and business stakeholders to deliver production-ready AI solutions.
Key Responsibilities
  • Design, build, train, evaluate, and deploy machine learning models.
  • Develop predictive models including churn, propensity, lead scoring, customer lifetime value, recommendation engines, forecasting, and marketing attribution.
  • Perform statistical analysis, hypothesis testing, causal inference, and A/B test analysis.
  • Build feature engineering and model training pipelines.
  • Deploy and monitor production ML models, including model drift detection and retraining.
  • Collaborate with Product, Engineering, Analytics, and executive leadership.
  • Mentor junior data scientists and establish best practices.

Required Qualifications
  • Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or related field, Master's or PhD preferred
  • 5+ years of experience building and deploying production ML systems, with a track record of measurable business impact
  • Strong communication and business problem-solving skills

Technical Skills
  • Expert Python and SQL
  • Machine Learning: XGBoost, LightGBM, Random Forests, Neural Networks, Deep Learning
  • Statistics: Regression, Bayesian methods, hypothesis testing, experimental design, time series, causal inference
  • Snowflake, Matillion, dbt, Pandas, Spark, Airflow
  • Cloud: Google Cloud (preferred), AWS, or Azure
  • MLOps: MLflow, Kubeflow, Vertex AI Pipelines, Feature Stores, CI/CD
  • Data quality and observability: Great Expectations, Monte Carlo, or similar frameworks
  • LLMs and AI: OpenAI, Gemini, Claude, LangChain, LangGraph, Semantic Kernel, RAG, vector databases

Preferred Experience
  • Large-scale customer data platforms
  • Marketing analytics and personalization
  • Automotive or SaaS industry experience
  • Real-time inference and streaming platforms

Success Metrics
  • Deliver production-ready ML models with measurable business impact
  • Improve prediction accuracy and operational efficiency
  • Implement model monitoring and retraining
  • Mentor team members and establish Data Science best practices
  • Contribute to team capability growth through documentation, code review standards, and mentorship outcomes that raise the overall quality of the Data Science function

COMPENSATION
Compensation commensurate on experience. Participation in company benefit offerings include medical, dental, vision, unlimited paid leave, 401(k) matching, wellness, and more. The expected salary range for this position is $160,000-$220,000 annually. The final offer will be based on several factors, including relevant experience, skills, and qualifications.
NEXT STEPS
If you meet the requirements, and are interested in applying for this role, please complete the online application, be sure to include a current resume and contact information. Local and remote candidates (living within Eastern or Central Time Zone) will be considered. No relocation assistance provided for this position. NO PHONE CALLS PLEASE.
About Team Velocity
Team Velocity is a full-service marketing agency serving the automotive industry, providing integrated marketing solutions to OEMs and dealerships nationwide. We leverage our proprietary Apollo® technology platform to predict consumer behavior, personalize marketing campaigns, and help dealerships drive more sales and service revenue.
Our team members are driven, creative, and collaborative, enjoying a unique culture where innovation and client success are paramount.
Join us in revolutionizing automotive marketing and technology through powerful, data-driven insights, continuous improvement, and an unwavering commitment to reliability.

Apply