Principal Data Scientist
Sioux Falls, SD · On-site
Qualifications * Master's or PhD in Data Science, Statistics, Mathematics, Computer Science ... Strong programming skills in Python, R, or similar analytical languages. * Extensive experience ...
Sioux Falls, SD · On-site
Qualifications * Master's or PhD in Data Science, Statistics, Mathematics, Computer Science ... Strong programming skills in Python, R, or similar analytical languages. * Extensive experience ...
Sioux Falls, SD · On-site
Qualifications * Master's or PhD in Data Science, Statistics, Mathematics, Computer Science ... Strong programming skills in Python, R, or similar analytical languages. * Extensive experience ...
Qualifications * Master's or PhD in Data Science, Statistics, Mathematics, Computer Science ... Strong programming skills in Python, R, or similar analytical languages. * Extensive experience ...
Qualifications * Master's or PhD in Data Science, Statistics, Mathematics, Computer Science ... Strong programming skills in Python, R, or similar analytical languages. * Extensive experience ...
Sioux Falls, SD · On-site
$125K/yr
Leading data science or statistical analysis initiatives by defining project scope, analytic ... R, Python, SAS, or equivalent tools, to support reproducible analysis, reporting, modeling, or ...
Sioux Falls, SD · On-site
$125K/yr
Leading data science or statistical analysis initiatives by defining project scope, analytic ... R, Python, SAS, or equivalent tools, to support reproducible analysis, reporting, modeling, or ...
Leading data science or statistical analysis initiatives by defining project scope, analytic ... R, Python, SAS, or equivalent tools, to support reproducible analysis, reporting, modeling, or ...
Leading data science or statistical analysis initiatives by defining project scope, analytic ... R, Python, SAS, or equivalent tools, to support reproducible analysis, reporting, modeling, or ...
The ideal candidate will have a Master's or PhD with extensive experience in data science and a strong command of programming languages like Python and R. Sedgwick offers a supportive culture and ...
The ideal candidate will have a Master's or PhD with extensive experience in data science and a strong command of programming languages like Python and R. Sedgwick offers a supportive culture and ...
Leverage experience and expertise in data science, analytics, and consumer finance to support the ... Expertise in SQL, SAS, Python, or R for data analysis and manipulation. * Experience with cloud ...
Leverage experience and expertise in data science, analytics, and consumer finance to support the ... Expertise in SQL, SAS, Python, or R for data analysis and manipulation. * Experience with cloud ...
Leverage experience and expertise in data science, analytics, and consumer finance to support the ... Expertise in SQL, SAS, Python, or R for data analysis and manipulation. * Experience with cloud ...
Leverage experience and expertise in data science, analytics, and consumer finance to support the ... Expertise in SQL, SAS, Python, or R for data analysis and manipulation. * Experience with cloud ...
Leverage experience and expertise in data science, analytics, and consumer finance to support the ... Expertise in SQL, SAS, Python, or R for data analysis and manipulation. * Experience with cloud ...
Leverage experience and expertise in data science, analytics, and consumer finance to support the ... Expertise in SQL, SAS, Python, or R for data analysis and manipulation. * Experience with cloud ...
Leverage experience and expertise in data science, analytics, and consumer finance to support the ... Expertise in SQL, SAS, Python, or R for data analysis and manipulation. * Experience with cloud ...
Leverage experience and expertise in data science, analytics, and consumer finance to support the ... Expertise in SQL, SAS, Python, or R for data analysis and manipulation. * Experience with cloud ...
Leverage experience and expertise in data science, analytics, and consumer finance to support the ... Expertise in SQL, SAS, Python, or R for data analysis and manipulation. * Experience with cloud ...
Leverage experience and expertise in data science, analytics, and consumer finance to support the ... Expertise in SQL, SAS, Python, or R for data analysis and manipulation. * Experience with cloud ...
$37.3K - $51.7K
2% of jobs
$51.7K - $66.1K
3% of jobs
$66.1K - $80.4K
6% of jobs
$80.4K - $94.8K
9% of jobs
$99.5K is the 25th percentile. Wages below this are outliers.
$94.8K - $109.2K
15% of jobs
The median wage is $118.8K / yr.
$109.2K - $123.6K
22% of jobs
$131.5K is the 75th percentile. Wages above this are outliers.
$123.6K - $138K
32% of jobs
$138K - $152.3K
3% of jobs
$152.3K - $166.7K
4% of jobs
$166.7K - $181.1K
1% of jobs
$181.1K - $195.5K
2% of jobs
$37.3K
$122.1K
$195.5K
A Data Science R job involves using the R programming language for data analysis, statistical modeling, and machine learning. Professionals in this role work with large datasets, clean and preprocess data, apply predictive modeling techniques, and visualize insights. They often use libraries like ggplot2, dplyr, and caret to manipulate data and build models. This role is common in industries such as finance, healthcare, and marketing, where data-driven decision-making is essential. Strong statistical knowledge, programming skills, and domain expertise are key to success in this position.
In most organizations, Data Science R professionals spend their days gathering and cleaning data, performing exploratory data analysis with R, building and evaluating predictive models, and generating data visualizations to communicate results. They often meet with cross-functional teams to understand business needs, translate them into data projects, and present key findings. Additionally, they may write reproducible R scripts, maintain data pipelines, and document their methodologies. Collaboration, experimentation, and clear communication are integral parts of the role, enabling solutions that directly impact business outcomes.
To thrive as a Data Science R professional, you need solid expertise in statistics, machine learning, and programming in R, often supported by a degree in data science, statistics, or a related field. Experience with R-based data analysis libraries, visualization tools like ggplot2, and familiarity with databases or cloud platforms is typically expected; certifications in data science or R programming can be advantageous. Strong problem-solving abilities, attention to detail, and effective communication with stakeholders help distinguish top performers in this role. These skills are essential for delivering actionable insights from complex datasets and driving data-informed decision-making within organizations.

Other
This job post has expired today. Applications are no longer accepted.
7.5
Based on 312 frontline employees who took The Breakroom Quiz
198th of 277 rated insurance
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