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Causal Inference Machine Learning Postdoctoral Jobs in Washington, DC

Machine Learning Engineer

Mclean, VA · On-site

$105K - $115K/yr

As a Machine Learning Engineer at Somatus, you will work collaboratively with our data and ... Perform exploratory data analysis, statistical modeling, causal inference, and other advanced ...

Senior Data Scientist

Herndon, VA · On-site +1

$160K - $190K/yr

Machine Learning: XGBoost, LightGBM, Random Forests, Neural Networks, Deep Learning * Statistics: Regression, Bayesian methods, hypothesis testing, experimental design, time series, causal inference

Senior Data Scientist

Herndon, VA · On-site +1

$160K - $190K/yr

Machine Learning: XGBoost, LightGBM, Random Forests, Neural Networks, Deep Learning * Statistics: Regression, Bayesian methods, hypothesis testing, experimental design, time series, causal inference

Experimentation and causal inference Own A/B tests end-to-end, from design and power analysis ... Applied machine learning Use standard ML techniques (classification, regression, clustering) where ...

Expertise in data analysis and machine learning, with experience applying these techniques in an educational context preferred. *Familiarity with experimental design and causal inference ...

They are seeking a Data Scientist to leverage advanced statistics, data analytics, machine learning ... Causal inference / uplift modeling / synthetic controls, Modern ML frameworks: LightGBM/XGBoost ...

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Causal Inference Machine Learning Postdoctoral information

See Washington, DC salary details

$40.2K

$61.4K

$69.1K

How much do causal inference machine learning postdoctoral jobs pay per year?

As of Jul 30, 2026, the average yearly pay for causal inference machine learning postdoctoral in Washington, DC is $61,413.00, according to ZipRecruiter salary data. Most workers in this role earn between $60,600.00 and $64,000.00 per year, depending on experience, location, and employer.

What is a Causal Inference Machine Learning Postdoctoral researcher?

A Causal Inference Machine Learning Postdoctoral researcher is a scientist who specializes in developing and applying machine learning methods to understand cause-and-effect relationships in data. They typically hold a recent PhD in statistics, computer science, economics, or a related field, and work in academic or industry research settings. Their work involves designing experiments, analyzing complex datasets, and creating models that can infer causal relationships, which are crucial for making robust predictions and informed decisions. This role often collaborates with interdisciplinary teams to apply these techniques to domains such as healthcare, social science, or economics.

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

To thrive as a Causal Inference Machine Learning Postdoctoral researcher, you need a strong background in statistics, causal inference methodologies, and advanced machine learning, usually evidenced by a PhD in a relevant field. Familiarity with programming languages such as Python or R, experience using statistical software (e.g., TensorFlow, PyTorch, Stan), and knowledge of causal inference libraries are typically required. Outstanding analytical thinking, problem-solving abilities, and strong communication skills help you collaborate effectively and explain complex concepts to diverse audiences. These skills and qualifications are vital for advancing research, deriving actionable insights from data, and contributing to impactful scientific discoveries.

What are some common challenges faced by Causal Inference Machine Learning Postdoctoral researchers when integrating causal models with real-world data?

Causal Inference Machine Learning Postdoctoral researchers often encounter challenges such as dealing with unobserved confounding variables, ensuring data quality, and addressing biases inherent in observational datasets. Integrating advanced machine learning techniques with causal inference frameworks requires careful consideration of model assumptions and validation methods. Collaboration with domain experts is essential to properly interpret results and to translate findings into actionable insights, especially in interdisciplinary settings like healthcare or social sciences.

What is the difference between Causal Inference Machine Learning Postdoctoral vs Data Scientist?

AspectCausal Inference Machine Learning PostdoctoralData Scientist
Required CredentialsPhD in statistics, machine learning, or related fieldBachelor's or Master's in data science, computer science, or related field
Work EnvironmentAcademic research, research labs, universitiesCorporate, tech companies, startups
Industry UsageResearch, academia, specialized industry projectsBusiness analytics, product development, data-driven decision making
Common Search/ComparisonYesYes

The main difference is that Causal Inference Machine Learning Postdoctoral roles focus on academic research and developing new methods in causal inference, often requiring a PhD. Data Scientists typically work in industry, applying existing models to solve business problems, with a focus on data analysis and visualization. While both roles involve machine learning, the postdoctoral position emphasizes research and theory, whereas data science emphasizes practical application.

What are popular job titles related to Causal Inference Machine Learning Postdoctoral jobs in Washington, DC? For Causal Inference Machine Learning Postdoctoral jobs in Washington, DC, the most frequently searched job titles are:
What job categories do people searching Causal Inference Machine Learning Postdoctoral jobs in Washington, DC look for? The top searched job categories for Causal Inference Machine Learning Postdoctoral jobs in Washington, DC are:
Infographic showing various Causal Inference Machine Learning Postdoctoral job openings in Washington, DC as of June 2026, with employment types broken down into 74% Full Time, 24% Part Time, and 2% Contract. Highlights an 91% Physical, 1% Hybrid, and 8% Remote job distribution, with an average salary of $61,413 per year, or $29.5 per hour.

Machine Learning Engineer

Somatus, Inc.

Mclean, VA • On-site

$105K - $115K/yr

Full-time

Medical, Dental, Vision, PTO

Posted 22 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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