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Remote Causal Inference Jobs in Wisconsin (NOW HIRING)

Lead advanced analytical techniques such as causal inference, scenario simulation, and risk scoring ... Strong mentoring and technical leadership capabilities. #LI-TS1 #remote Sedgwick is an Equal ...

Remote Causal Inference information

What are the key skills and qualifications needed to thrive as a Remote Causal Inference Specialist, and why are they important?

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 is a Remote Causal Inference job?

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 most commonly searched types of Causal Inference jobs in Wisconsin? The most popular types of Causal Inference jobs in Wisconsin are:
What cities in Wisconsin are hiring for Remote Causal Inference jobs? Cities in Wisconsin with the most Remote Causal Inference job openings:
Infographic showing various Remote Causal Inference job openings in Wisconsin as of May 2026, with employment types broken down into 3% Locum Tenens, 2% Internship, 40% Full Time, 9% Part Time, 45% Contract, and 1% Nights. Highlights an 79% Physical, 3% Hybrid, and 18% Remote job distribution.
Principal Data Scientist

Principal Data Scientist

Sedgwick

Milwaukee, WI • On-site, Remote

Other

Posted 17 days ago


Sedgwick rating

7.5

Company rating: 7.5 out of 10

Based on 305 frontline employees who took The Breakroom Quiz

193rd of 260 rated insurance


Job description

By joining Sedgwick, you'll be part of something truly meaningful. It's what our 33,000 colleagues do every day for people around the world who are facing the unexpected. We invite you to grow your career with us, experience our caring culture, and enjoy work-life balance. Here, there's no limit to what you can achieve.

Newsweek Recognizes Sedgwick as America's Greatest Workplaces National Top Companies

Certified as a Great Place to Work®

Fortune Best Workplaces in Financial Services & Insurance

Principal Data Scientist

Job Responsibilities

  • Lead the design and development of advanced statistical and machine learning models that improve claims outcomes, operational efficiency, and risk management.

  • Serve as the technical authority for complex modeling initiatives including fraud detection, claims severity prediction, litigation risk modeling, and recovery optimization.

  • Develop predictive and prescriptive models using structured and unstructured claims data, including adjuster notes, medical records, and policy documentation.

  • Architect modeling approaches that leverage modern techniques such as gradient boosting, deep learning, NLP, anomaly detection, and probabilistic modeling.

  • Partner with AI Engineering teams to productionize models and integrate them into enterprise AI platforms and operational systems.

  • Design feature engineering strategies and modeling pipelines using large-scale enterprise datasets.

  • Establish best practices for model development, experimentation, validation, and reproducibility.

  • Lead advanced analytical techniques such as causal inference, scenario simulation, and risk scoring methodologies.

  • Build and maintain model evaluation frameworks that measure accuracy, bias, stability, and business impact.

  • Monitor deployed models for drift, degradation, and changing data distributions, and recommend recalibration strategies.

  • Provide technical guidance to data scientists and analysts across the organization.

  • Mentor junior team members on statistical methods, machine learning techniques, and analytical rigor.

  • Translate complex analytical findings into clear, actionable insights for business leaders and operational teams.

  • Collaborate with Claims Operations, Finance, Risk, and IT stakeholders to identify high-impact analytical opportunities.

  • Evaluate external data sources and third-party analytical solutions that enhance predictive capabilities.

  • Ensure analytical methodologies align with enterprise governance standards and regulatory expectations.

  • Contribute to Sedgwick's broader AI and advanced analytics strategy by identifying emerging technologies and modeling approaches.

  • Lead research and innovation initiatives that advance Sedgwick's predictive analytics capabilities.

Qualifications

  • Master's or PhD in Data Science, Statistics, Mathematics, Computer Science, Economics, or related quantitative discipline.

  • 8-12+ years of experience in data science, statistical modeling, or advanced analytics roles.

  • Deep expertise in machine learning algorithms, statistical modeling techniques, and predictive analytics methodologies.

  • Strong programming skills in Python, R, or similar analytical languages.

  • Extensive experience working with large, complex datasets in enterprise environments.

  • Proven experience designing and implementing end-to-end modeling pipelines.

  • Strong understanding of model validation, feature engineering, and performance evaluation techniques.

  • Experience collaborating with engineering teams to deploy models into production systems.

  • Familiarity with distributed data processing tools and modern data platforms preferred.

  • Experience in insurance, claims management, healthcare, or financial services analytics preferred.

  • Ability to communicate advanced analytical concepts to both technical and non-technical stakeholders.

  • Demonstrated ability to lead complex analytical initiatives that drive measurable business value.

  • Strong mentoring and technical leadership capabilities.

#LI-TS1 #remote

Sedgwick is an Equal Opportunity Employer and a Drug-Free Workplace.

If you're excited about this role but your experience doesn't align perfectly with every qualification in the job description, consider applying for it anyway! Sedgwick is building a diverse, equitable, and inclusive workplace and recognizes that each person possesses a unique combination of skills, knowledge, and experience. You may be just the right candidate for this or other roles.

Sedgwick is the world's leading risk and claims administration partner, which helps clients thrive by navigating the unexpected. The company's expertise, combined with the most advanced AI-enabled technology available, sets the standard for solutions in claims administration, loss adjusting, benefits administration, and product recall. With over 33,000 colleagues and 10,000 clients across 80 countries, Sedgwick provides unmatched perspective, caring that counts, and solutions for the rapidly changing and complex risk landscape. For more, see sedgwick.com


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