Remote Senior Data Scientist & ML Strategy Lead

Sedgwick

United States

Remote

USD 140,000 - 200,000

Full time

14 days+

Application generator

Stand out for this role — generate a tailored resume and cover letter in about a minute.

Get past ATS filters

Job summary

Sedgwick seeks a Principal Data Scientist to lead advanced modeling efforts across claims, risk, and operational analytics. You will design scalable ML solutions and guide cross‑functional teams in productionizing models.

This role requires deep ML expertise, mentoring, and strong communication with technical and business stakeholders. Remote-friendly US-based role with enterprise impact on analytics and decision making.

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.
Experience 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.
Familiarity with distributed data processing tools and modern data platforms.
Experience in insurance/claims analytics or financial services is preferred.
Ability to communicate complex analytical concepts to technical and non-technical stakeholders.
Demonstrated ability to lead complex analytical initiatives delivering measurable business value.
Strong mentoring and technical leadership capabilities.

Responsibilities

Lead the design and development of advanced statistical and machine learning models to improve claims outcomes and risk management.
Serve as the technical authority for complex modeling initiatives including fraud detection and claims severity prediction.
Develop predictive and prescriptive models using structured and unstructured claims data.
Architect modeling approaches leveraging gradient boosting, deep learning, NLP, anomaly detection, and probabilistic modeling.
Partner with AI Engineering teams to productionize models and integrate them into enterprise platforms.
Design feature engineering strategies and pipelines using large-scale datasets.
Establish best practices for model development, experimentation, validation, and reproducibility.
Lead advanced analytical techniques such as causal inference and risk scoring methodologies.
Build and maintain model evaluation frameworks to measure accuracy and business impact.
Monitor deployed models for drift and degradation; recommend recalibration strategies.
Provide technical guidance to data scientists and analysts across the organization.
Mentor junior team members on statistical methods and analytics.
Translate complex findings into clear, actionable insights for leaders and operational teams.
Collaborate with Claims Operations, Finance, Risk, and IT stakeholders to identify high-impact opportunities.
Evaluate external data sources and third-party analytics solutions to enhance predictive capabilities.
Ensure methodologies align with governance standards and regulatory expectations.
Contribute to Sedgwick's broader AI strategy and identify emerging technologies.
Lead research and innovation initiatives advancing predictive analytics capabilities.