Lead design of statistical and machine learning models for claims outcomes and risk
Develop predictive models from structured and unstructured claims data
Partner with AI Engineering to productionize and integrate models
Monitor deployed models for drift and recommend recalibration
Mentor junior team members and guide data scientists on methods
From the employer’s posting
Lead the design and development of advanced statistical and machine learning models that improve claims outcomes, operational efficiency, and risk management.
Develop predictive and prescriptive models using structured and unstructured claims data, including adjuster notes, medical records, and policy documentation.
Partner with AI Engineering teams to productionize models and integrate them into enterprise AI platforms and operational systems.
Monitor deployed models for drift, degradation, and changing data distributions, and recommend recalibration strategies.
Mentor junior team members on statistical methods, machine learning techniques, and analytical rigor.
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.
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.
Preferred experience
Familiarity with distributed data processing tools and modern data platforms preferred.
Experience in insurance, claims management, healthcare, or financial services analytics preferred.
Qualification wording
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.
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.
Education & alternatives
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.
Open 6 monthsWe first saw this posting 180 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
Status in our records
Live
First seen by us
May 7, 2026180 days ago
Recorded sightings
287
Last seen by us
Nov 4, 2026
Employer says posted
Apr 30, 2026
May 7, 2026today
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Pay
$118K–$193K is typical
$118K$193K
The middle half of what similar US postings state. This one doesn’t list pay.
From 3,721 postings in the last year. Stated ranges, not salaries paid.
Time since we first saw it
Day 180
755
Up longer than most. Similar jobs usually come down between day 7 and day 55.
From 10,000 similar postings that came down. Coming down is not always a hire.
Sedgwick is hiring
13 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
Python
R
Where the posting names them
- 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.
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We file this job under Data Scientist, by the work the posting describes.
Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.
Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.
Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.
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.