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Causal Inference Phd Internship Jobs in Washington

Somatus, Inc.

Machine Learning Engineer

Mclean, VA · On-site

$105K - $115K/yr

Perform exploratory data analysis, statistical modeling, causal inference, and other advanced ... role, or PhD * At least 1 year of experience with Python * Some experience with relational ...

Vantor

Lead Data Scientist - TS/SCI

Herndon, VA · On-site

Direct graph analytics and causal inference activities. * Lead explainable AI implementation ... Master's or PhD in Computer Science, Data Science, Applied Mathematics, Physics, Operations ...

Maxar

Lead Data Scientist - TS/SCI

Herndon, VA

Direct graph analytics and causal inference activities. * Lead explainable AI implementation ... Master's or PhD in Computer Science, Data Science, Applied Mathematics, Physics, Operations ...

Vantor

Lead Data Scientist - TS/SCI

Herndon, VA · On-site

Direct graph analytics and causal inference activities. * Lead explainable AI implementation ... Master's or PhD in Computer Science, Data Science, Applied Mathematics, Physics, Operations ...

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Causal Inference Phd Internship information

What is a causal inference PhD internship?

A Causal Inference PhD Internship is a specialized research position for doctoral students focused on causal inference, which involves determining cause-and-effect relationships from data. Interns typically work with large datasets, advanced statistical models, and machine learning techniques to answer questions about how variables influence one another. These internships are often offered by tech companies, research labs, or policy organizations and provide hands-on experience in designing experiments, analyzing observational data, and developing new methodologies. The goal is to bridge academic research with real-world applications, contributing to projects that require rigorous causal analysis.

What types of projects does a causal inference PhD intern typically work on during their internship?

Causal Inference PhD interns often engage in projects that involve designing and analyzing experiments or observational studies to draw valid conclusions about cause-and-effect relationships. These projects might include developing statistical models, collaborating with data scientists and product teams, and presenting findings to inform business or policy decisions. Interns usually have the opportunity to work with large-scale, real-world data, and are encouraged to publish or present their work at conferences, supporting both professional growth and academic development.

What are the key skills and qualifications needed to thrive as a causal inference PhD intern, and why are they important?

To thrive as a Causal Inference PhD Intern, you need a strong background in statistics, econometrics, and causal inference methods, often supported by advanced graduate studies in a related field. Familiarity with statistical programming languages such as R or Python, and experience using data analysis tools and frameworks like Stata or TensorFlow Probability, are typically required. Excellent problem-solving abilities, critical thinking, and the ability to communicate complex concepts clearly help you stand out in this role. These skills and qualities are crucial for designing robust experiments, drawing reliable conclusions, and effectively collaborating with interdisciplinary research teams.

What is the difference between Causal Inference Phd Internship vs Data Scientist Internship?

AspectCausal Inference Phd InternshipData Scientist Internship
Required CredentialsPhD in statistics, economics, or related fieldBachelor's or Master's in CS, statistics, or related field
Work EnvironmentResearch-focused, academic or industry research teamsData analysis, modeling, and business insights
Employer & Industry UsageResearch institutions, tech companies, financeTech firms, startups, finance, healthcare
Search & Comparison IntentFocus on causal inference research rolesBroader data analysis roles

While a Causal Inference Phd Internship emphasizes research in causal analysis with advanced credentials, a Data Scientist Internship covers broader data analysis skills suitable for various industries. Both roles involve working with data, but their focus, required background, and career paths differ significantly.

What are popular job titles related to Causal Inference Phd Internship jobs in Washington?

For Causal Inference Phd Internship jobs in Washington, the most frequently searched job titles are:

What job categories do people searching Causal Inference Phd Internship jobs in Washington look for?

The top searched job categories for Causal Inference Phd Internship jobs in Washington are:

What cities in Washington are hiring for Causal Inference Phd Internship jobs?

Cities in Washington with the most Causal Inference Phd Internship job openings:

Causal Inference Phd Internship jobs near you
Infographic showing various Causal Inference Phd Internship job openings in Washington as of August 2026, with employment types broken down into 8% Internship, 58% Full Time, 26% Part Time, 3% Temporary, and 5% Contract. Highlights an 73% Physical, 2% Hybrid, and 25% Remote job distribution.

Machine Learning Engineer

Somatus, Inc.

Mclean, VA • On-site

$105K - $115K/yr

Full-time

Medical, Dental, Vision, PTO

Re-posted 13 days ago

Somatus rating

6.7

Company rating: 6.7 out of 10

Based on 15 frontline employees who took The Breakroom Quiz

Job description

How We Show Up for Our Patients:
As a leading provider of outcomes-driven care for individuals and communities living with chronic conditions, Somatus is helping patients across the country enjoy More Healthy Days at Home™.
Care at Somatus goes beyond treatment. Through a whole-person approach, we deliver outcomes-driven integrated care and show up #SomatusStrong for our patients and teammates. We partner closely with health plans, health systems, and provider groups to support patients with, or at risk of developing, cardio, kidney, metabolic, or other chronic conditions.
We hire the brightest and boldest - talent driven by purpose and impact. Since our founding in 2016, our growth trajectory isn't just a milestone - it's a signal. Our leadership values culture and leads with intention as we remain dedicated to driving clinical excellence.
Does this sound like you? Keep reading.
How We'll Support You:
We offer 25+ health, growth, and wealth work perks to help teammates be the best version of themselves, including:
  • Subsidized personal healthcare coverage: Medical, Dental & Vision, plus Wellness programs
  • Paid Time Off: Flexible PTO
  • Professional development: CEU and tuition reimbursement

How You'll Make an Impact:
Somatus is on a mission to be the world's best provider of integrated care for patients with or at risk of developing kidney disease. A core component of our mission is the effective and impactful use of data to support patient care. As a Machine Learning Engineer at Somatus, you will work collaboratively with our data and technology teams to help clinical, operational, and financial partners solve advanced analytical problems. Our culture is data-driven, collaborative, results-focused, and fast-moving.
If you have a passion for building things and using data to impact the lives of patients, families, and communities, then we want to speak with you!
  • Partner with ML engineers, data engineers, software developers, product managers, data analysts, and clinical and operations team members to deliver machine learning solutions that make an impact.
  • Assist with end-to-end lifecycle for AI and machine learning projects, including idea generation, data and feature engineering, model training, model evaluation, model testing, model deployment, model monitoring, and maintenance.
  • Build pipelines for training, evaluating, and deploying models.
  • Perform exploratory data analysis, statistical modeling, causal inference, and other advanced analytical techniques to uncover meaningful insights.
  • Advise stakeholders on experimentation best practices and help design and implement A/B/n testing as needed.
  • Stay current with trends and developments in the AI, machine learning, and healthcare technology communities.

How You'll Strengthen Our Team:
Qualifications:
  • Bachelor's or Master's Degree with 1 or more years of experience in a machine learning-related role, or PhD
  • At least 1 year of experience with Python
  • Some experience with relational databases and SQL
  • Understanding of software engineering best practices and software development lifecycle
  • Familiarity with Git and issue tracking tools such as JIRA
  • Familiarity with Linux and CLI

Preferred Qualifications:
  • Experience in healthcare industry and working with healthcare data
  • Experience with cloud infrastructure (Azure, AWS, or GCP)
  • Experience with Docker
  • Experience with Natural Language Processing
  • Experience with effectiveness research

Compensation:
$105,000 to $115,000 per year
We offer competitive compensation that reflects market conditions and recognizes the skills, experience, and contributions of our team members. Compensation for the role will depend on a number of factors, including a candidate's qualifications, skills, competencies, experience, and geographic location and may fall outside of the range shown above. In addition, this position may be eligible for a discretionary performance-based bonus in accordance with the Company's applicable incentive compensation plans.
This job description is not designed to cover or contain a comprehensive listing of activities, duties, or responsibilities required of the employee. Duties, responsibilities, and activities may change at any time with or without notice. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
Our Commitment to Diversity:
At Somatus, we celebrate what makes us unique - our people. We believe that a culture intentionally built to foster and support our unique passions, experiences, and perspectives helps fuel us in the pursuit of our mission.
Somatus, Inc. provides equal employment opportunity to all individuals regardless of race, color, creed, religion, gender, age, sexual orientation, national origin, disability, veteran status, or any other characteristic protected by law. Discrimination of any type will not be tolerated.

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