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MSIG USA

Commercial P&C insurance and risk management

Director of Insurance Analytics

Data ScienceConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • A bachelor's degree in Statistics, Computer Science, Mathematics, Economics, or a related quantitative field, or equivalent practical experience.
  • At least 7 years of experience in analytics or data science, with a track record of delivering measurable business impact.
  • At least 2 years leading analytics initiatives and/or mentoring technical team members in a senior or lead capacity.
  • Proficiency in Python and SQL, including the ability to write production-quality analytical code and review others’ work.
  • Ability to influence senior stakeholders and translate technical work into clear decisions, actions, and tradeoffs.

Responsibilities

  • Lead a portfolio of analytics and data science initiatives, owning work end-to-end from problem framing, prioritization, delivery planning, and stakeholder alignment through measurable business outcomes.
  • Translate ambiguous business questions into clear problem statements, hypotheses, and structured analytical approaches that influence decisions and operations.
  • Define success metrics and measurement plans, including benefit estimation, and track adoption and impact over time.
  • Drive cross-functional delivery across Underwriting, Pricing, Claims, and Actuarial; ensure solutions are practical, adopted, and aligned to business priorities.
  • Partner with business leaders to align work to decision needs, manage tradeoffs transparently, and maximize impact.
  • Write and review code in Python and SQL; build analytical prototypes, reusable analytics assets, and decision-support tools; and unblock technical decisions.
  • Apply statistical and machine learning techniques, including regression, classification, clustering, and time series, to solve business problems and support decision-making.
  • Develop and deploy solutions in a cloud-based analytics environment, partnering with platform and engineering teams to operationalize outputs into business workflows and drive sustained adoption.
  • Design and execute experiments and tests, as appropriate to the use case, to evaluate interventions, quantify impact, and support decision-making.
  • Define and reinforce production-minded analytical quality practices and standards appropriate to the use case, including validation, testing and controls, documentation, reproducible code, and operational transition plans for ongoing use.
  • Establish monitoring expectations appropriate to the solution, such as usage, data quality, and model performance, and drive continuous improvement based on signals.
  • Lead and contribute to solutions that improve underwriting and pricing decisions, such as portfolio diagnostics, segmentation and feature development, and workflow decision support, partnering with business leaders to drive adoption and measurable impact.
  • Support implementation of analyses and models into decisions and processes by educating stakeholders on intent, limitations, and appropriate use, and by providing practical documentation and tooling.
  • Communicate findings to technical and non-technical audiences and translate insights into concrete actions, process changes, or product improvements.
  • Partner with Claims leadership to identify and deliver analytics and decision-support opportunities that improve operational effectiveness and outcomes.
  • Support claims analytics data enablement with data and technology teams; translate claims workflows into analytics-ready measures and repeatable decision support and reporting.
  • Where applicable, help operationalize and monitor analytical solutions used in claims decisioning and workflows.
  • Serve as a trusted thought partner to senior stakeholders, facilitate working sessions, and manage tradeoffs transparently.
  • Produce executive-ready narratives that connect analytical evidence to decisions, risks, and tradeoffs.
  • Mentor data scientists and analysts on problem structuring, technical approach, and effective communication.
  • As scope expands, help build the team through hiring, onboarding, and talent development; responsibilities may evolve into formal people leadership.
  • Collaborate with technology and data platform teams to enable responsible deployment and operation of analytics solutions, including access, security, maintainability, and monitoring expectations appropriate to the solution, without owning enterprise platforms.
  • Define reusable patterns for analytics delivery, including templates, review checklists, and documentation standards, to reduce friction and improve time-to-value.

Desired Qualifications

  • A bachelor's or master's degree in Statistics, Mathematics, Computer Science, Engineering, or Economics, or a related field, or equivalent practical experience.
  • Property and Casualty insurance experience, preferably commercial lines, or demonstrated ability to ramp quickly in complex domains.
  • Experience productionizing analytics or model outputs in partnership with engineering teams, such as APIs or services, CI/CD, and containerization.
  • Experience with cloud-based analytics environments and modern machine learning frameworks such as scikit-learn and XGBoost.
  • Experience with experimentation, causal inference, or rigorous measurement approaches in business settings.
  • Experience establishing monitoring practices appropriate to the solution, such as model performance, data quality, and usage or adoption.
  • Familiarity with business intelligence tools such as Power BI and Tableau, and data visualization best practices.
  • A track record of mentoring, coaching, and/or managing technical teams.

About the Company

MSIG USA

Commercial P&C insurance and risk management

MSIG USA provides commercial property and casualty insurance to U.S.-based and multinational businesses, with tailored coverage across property, casualty, marine, and financial lines (including D&O and cyber). It writes standard policies and specialized programs, and has recently established MSIG Specialty Insurance America to underwrite non-admitted business. A core part of its model is risk engineering, loss prevention, and in-house claims management (handling over 90% of claims directly) to deliver efficient service. The company differentiates itself through the backing of the MS&AD Insurance Group (a financially strong parent), a history of large-scale P&C capacity, and a focus on customized solutions for complex exposures. Its goal is to help organizations manage sophisticated risks across all 50 states, including multinational clients, by offering comprehensive coverage and proactive risk management.

Company size
501-1,000
Company stage
Not listed
Total funding
Not listed
Headquarters
New York City, New York
Founded
Not listed

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