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Causal Inference Jobs in North Carolina (NOW HIRING)

Guidehouse

Biostatistician Lead

Charlotte, NC · On-site

Guide methodological decisions related to study design, causal inference, quasi-experimental methods, observational studies, and evaluation frameworks. * Lead development and validation of ...

Duke University

Postdoctoral Associate

Durham, NC

Familiarity with causal inference methods or machine learning approaches * Demonstrated experience in scientific writing and publication Ideal for candidates who: * Have recently completed (or are ...

Duke University

Postdoctoral Associate

Durham, NC · On-site

Familiarity with causal inference methods or machine learning approaches * Demonstrated experience in scientific writing and publication Ideal for candidates who: * Have recently completed (or are ...

Epic Games

Senior Data Scientist

Cary, NC · On-site

Experience with causal inference methods * Passion for the gaming industry EPIC JOB + EPIC BENEFITS = EPIC LIFE Our intent is to cover all things that are medically necessary and improve the quality ...

Epic Games

Senior Data Scientist

Cary, NC · On-site

Experience with causal inference methods * Passion for the gaming industry EPIC JOB + EPIC BENEFITS = EPIC LIFE Our intent is to cover all things that are medically necessary and improve the quality ...

Guidehouse

Epidemiologist Data Scientist

Charlotte, NC

$80K - $133K/yr

Experience with survey data, weighting methodologies, causal inference, or advanced statistical methods. * Experience using Databricks, Snowflake, Palantir Foundry, Azure, or similar cloud platforms.

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Causal Inference information

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$50K

$90.2K

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How much do causal inference jobs pay per year?

As of Aug 20, 2026, the average yearly pay for causal inference in North Carolina is $90,181.00, according to ZipRecruiter salary data. Most workers in this role earn between $78,200.00 and $98,600.00 per year, depending on experience, location, and employer.

What is a causal inference?

A Causal Inference job involves using statistical and computational methods to determine cause-and-effect relationships from data. Professionals in this field work with observational and experimental data to identify causal impacts, often in domains like economics, healthcare, social sciences, and technology. They apply techniques such as propensity score matching, instrumental variables, and difference-in-differences to ensure rigorous analysis. These roles are commonly found in academia, policy research, and data science teams within tech and finance companies. Strong skills in statistics, programming (e.g., Python, R), and experimental design are typically required.

What skills and qualifications are needed for a causal inference position?

Success in a Causal Inference role requires strong statistical knowledge, expertise in experimental and quasi-experimental methodologies, and advanced proficiency in programming languages like R or Python, typically acquired with an advanced degree in statistics, economics, data science, or a related field. Familiarity with specialized statistical software (such as Stata, SAS, or causal inference packages in R/Python), as well as experience with large datasets and machine learning tools, is highly valued. Excellent problem-solving abilities, clear communication, and collaboration skills are essential soft skills for effectively conveying complex findings to diverse teams. These competencies are critical to producing reliable insights that guide evidence-based decision-making in business, healthcare, or policy settings.

What are common challenges faced in a causal inference position?

Professionals in Causal Inference often encounter challenges such as dealing with confounding factors, addressing selection bias, and ensuring the validity of assumptions behind statistical models. They must carefully design experiments or leverage observational data while staying vigilant about potential data quality issues and model limitations. Collaboration with subject matter experts, data engineers, and business stakeholders is common to ensure accurate contextualization of results. Overcoming these challenges requires a mix of technical acumen and strong communication skills to translate complex analyses into actionable recommendations.

What are the most commonly searched types of Causal Inference jobs in North Carolina?

The most popular types of Causal Inference jobs in North Carolina are:

What are popular job titles related to Causal Inference jobs in North Carolina?

For Causal Inference jobs in North Carolina, the most frequently searched job titles are:

What job categories do people searching Causal Inference jobs in North Carolina look for?

The top searched job categories for Causal Inference jobs in North Carolina are:

What cities in North Carolina are hiring for Causal Inference jobs?

Cities in North Carolina with the most Causal Inference job openings:

Causal Inference jobs near you
Infographic showing various Causal Inference job openings in North Carolina as of August 2026, with employment types broken down into 78% Full Time, 14% Part Time, 7% Temporary, and 1% Contract. Highlights an 67% Physical, 4% Hybrid, and 29% Remote job distribution, with an average salary of $90,181 per year, or $43.4 per hour.

Principal Data Scientist (Raleigh)

Azurity Pharmaceuticals

Raleigh, NC • On-site

$180K - $220K/yr

Full-time

Medical, Dental, Vision

Re-posted 18 days ago

Job description

Base pay range

$180,000.00/yr - $220,000.00/yr


Additional compensation types

Annual Bonus


About the Company

Azurity Pharmaceuticals is a privately held, specialty pharmaceutical company that focuses on innovative products that meet the needs of underserved patients. As an industry leader in providing unique, accessible, and high-quality medications, Azurity leverages its integrated capabilities and vast partner network to continually expand its broad commercial product portfolio and robust late-stage pipeline. The company’s patient centric products span the cardiovascular, neurology, endocrinology, gastro-intestinal, institutional, and orphan markets, and have benefited millions of patients. For more information, visit www.azurity.com. Azurity Pharmaceuticals is proud to be an inclusive workplace and an Equal Opportunity Employer. Azurity's success is attributable to our incredibly talented, dedicated team that focuses on benefiting the lives of patients by bringing the best science and commitment to quality into everything that we do. We seek highly motivated individuals with the dedication, integrity, and creative spirit needed to thrive in our organization.


About the Role

Azurity Pharmaceuticals is seeking a Principal Data Scientist to lead the design, strategic development and operationalization of advanced analytics and AI/Machine Learning solutions that directly drive commercial impact across our portfolio. This is a high-visibility, high-impact role that combines hands-on data science leadership with strategic influence, helping to shape the future of commercial analytics at Azurity. You will serve as a hands-on technical contributor and scientific thought leader across a range of innovative machine learning, statistical modeling, causal inference, and decision optimization models. These models will power initiatives across field sales, omnichannel marketing, HCP engagement, and strategic account management—You will work in close collaboration with data engineering, business strategy, field operations, and executive stakeholders to translate business objectives into deployable, scalable models that optimize brand performance and patient access. The ideal candidate is not only a deep expert in applied data science but also a forward thinking leader with a track record of driving business value through scalable AI systems, mentoring teams, and setting long-term analytics direction.


Responsibilities

  • Set the strategy and lead the execution of Azurity’s commercial analytics and AI roadmap, aligning data science initiatives with corporate growth

  • Own the end-to-end development lifecycle for machine learning and causal inference models that inform:

  • Omnichannel marketing targeting and optimization

  • Strategic account prioritization

  • Design and implement causal modeling frameworks (e.g., uplift modeling, counterfactuals, quasi-experiments), Observational causal inference techniques, including Propensity Score Matching (PSM), inverse probability weighting, and doubly robust estimators to quantify true business impact

  • Drive adoption of best practices in model governance, MLOps, reproducibility, and documentation using tools like Git, DBT, MLflow, and Azure

  • Serve as a technical mentor and team leader, guiding junior and senior scientists and elevating standards in modeling rigor, code quality, and business alignment

  • Collaborate cross-functionally with Commercial Strategy, Marketing, Field Operations, and Executive Leadership to frame problems as scalable modeling solutions

  • Influence platform and tooling decisions, with a focus on Azure-based infrastructure, Palantir Foundry, and CRM integration (Salesforce)

  • Stay ahead of industry trends and bring innovative methodologies into Azurity’s data science toolkit—especially in GenAI, personalization, and intelligent automation


Qualifications

  • Advanced degree (PhD or MS) in a quantitative field such as Statistics, Data Science, Computer Science, Applied Mathematics, Physics, Engineering, or a related STEM discipline

  • 7+ years of applied experience in data science, advanced analytics, machine learning or AI roles, including experience in the pharmaceutical or life sciences industry or commercial analytics is strongly preferred

  • Demonstrated expertise in:

  • Causal inference, uplift modeling, and experimental design, Bayesian methods, un-/supervised learning etc.

  • Machine learning techniques (tree-based models, ensembles, neural nets, etc.)

  • Python, PySpark, SQL, Git, and data workflow tools (DBT, Airflow, etc.)

  • Experience with modern data platforms such as Snowflake, Palantir Foundry, or equivalent

  • Proven ability to translate complex modeling outputs into actionable business insights

  • Deep familiarity with Azure cloud services for model development and deployment

  • Experience integrating and modeling with CRM and sales data (e.g., Salesforce)

  • Strong communication and stakeholder management skills, with experience influencing non-technical audiences and strong presentation skills


Required Skills

  • Experience defining and executing strategic analytics roadmaps across commercial functions

  • Prior management or team leadership experience, including mentoring, hiring, and developing data scientists

  • Background in AI/ML-driven forecasting, resource optimization, and business impact modeling

  • Familiarity with marketing technology, personalization systems, recommender engines, and ROI modeling

  • Experience with GenAI, prompt engineering, RAG, and autonomous/agentic systems or multi-ai agent systems for commercial use

  • Knowledge of Reinforcement Learning (RL) and sequential decision-making frameworks


Pay range and compensation package

Unlock Your Earning Potential: Join our team and be rewarded with a competitive compensation package, including an annual bonus based on company performance, that recognizes your exceptional talent.



  • Sales - In lieu of annual bonuses, we offer an Incentive compensation program that allows you to earn more - even over plan.

  • Fuel Your Success: *Sales Only* - We understand the value of your hard work and provide a car reimbursement program and gas card for both business and personal use as part of our commitment to supporting you.


Equal Opportunity Statement

Azurity Pharmaceuticals is proud to be an inclusive workplace and an Equal Opportunity Employer. We are committed to diversity and inclusivity.


Benefits We Offer

  • Comprehensive Health Coverage: We value your well-being and offer excellent medical, dental, vision, and prescription coverage to ensure you and your family are always taken care of.

  • Flexibility for Your Lifestyle: Achieve work-life


Seniority level

Director


Employment type

Full-time


Industries

Pharmaceutical Manufacturing

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