Director of Insurance Analytics

Job Purpose

MSIG USA, part of the MS&AD group, is looking for a hands‑on analytics Manager/Director to lead a portfolio of high‑impact initiatives, drive cross‑functional delivery, and build analytical solutions that influence underwriting, pricing, claims, and actuarial functions. The candidate will own the full analytics lifecycle – from problem framing and hypothesis definition to experimentation, modeling, and operationalization.

Location

NYC / Warren, NJ / OR Philadelphia, PA (Hybrid – 4 days in office; remote considered in exceptional circumstances).

Essential Functions

• Lead a portfolio of analytics & data science initiatives, owning problem framing, prioritization, delivery planning, stakeholder alignment, and measurable business outcomes.
• Translate ambiguous business questions into clear problem statements, hypotheses, and structured analytical approaches that influence decisions and operations.
• Define success metrics, 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 closely with business leaders to align work to decision needs, manage trade‑offs transparently, and maximize impacts.
• Write and review code (Python & SQL), build analytical prototypes, reusable analytics assets, and decision‑support tools, and unblock technical decisions.
• Apply statistical and machine learning techniques (regression, classification, clustering, time series) to solve business problems and support decision‑making.
• Develop and deploy solutions in a cloud‑based analytics environment, collaborating with platform and engineering teams to operationalize outputs into business workflows.
• Design and execute experiments and tests to evaluate interventions, quantify impact, and support decision‑making.
• Establish production‑minded practices and standards for analytical quality (validation, testing/control, documentation, reproducible code, operational transition).
• Set monitoring expectations (usage, data quality, model performance) and drive continuous improvement.
• Deliver decision support for underwriting and pricing/actuarial, improving underwriting decisions, segmentation, and workflow decision support.
• Educate stakeholders on model intent, limitations, and appropriate use; provide practical documentation and tooling.
• Communicate findings clearly to both technical and non‑technical audiences; translate insights into concrete actions, process changes, or product improvements.
• Partner with claims leadership to identify and deliver high‑value analytics and decision support opportunities that improve operational effectiveness.
• Support data enablement for claims analytics, translating workflows into analytics‑ready measures and repeatable decision support and reporting.
• 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 trade‑offs transparently.
• Produce executive‑ready narratives that connect analytical evidence to decisions, risks, and trade‑offs.
• Mentor data scientists/analysts on problem structuring, technical approach, and communication.
• Over time, 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 (access, security, maintainability, monitoring).
• Help define reusable analytics delivery patterns (templates, review checklists, documentation standards) that reduce friction and improve time‑to‑value.

Supervisory Responsibilities

• Position is a hands‑on program/initiative lead and may include people leadership; scope and people‑management responsibilities will vary by final level (Manager vs Director) and organizational needs.

Qualifications

• Bachelor’s degree in Statistics, Computer Science, Mathematics, Economics, or a related quantitative field (or equivalent experience).
• 7+ years of analytics or data science experience with a track record of delivering measurable business impact.
• 2+ years leading analytics initiatives and/or mentoring technical team members in a senior/lead capacity.
• Proficiency in Python and SQL; ability to write production‑quality analytical code and review others’ work.
• Strong communication skills with ability to influence senior stakeholders; translate technical work into clear decisions, actions, and trade‑offs.

Preferred Qualifications

• Bachelor’s or Master’s degree in Statistics, Mathematics, Computer Science, Engineering, Economics, or related field (or equivalent experience). Property & Casualty insurance experience (commercial lines preferred) or demonstrated ability to ramp quickly in complex domains.
• Experience productionizing analytics/model outputs in partnership with engineering teams (APIs/services, CI/CD, containerization).
• Experience with cloud‑based analytics environments and modern ML frameworks (scikit‑learn, XGBoost).
• Experience with experimentation, causal inference, or rigorous measurement approaches in business settings.
• Experience establishing monitoring practices appropriate to the solution (model performance, data quality, usage/adoption).
• Familiarity with BI tools (Power BI, Tableau) and data visualization best practices.
• Track record of mentoring, coaching, and/or managing technical teams.

Salary and Benefits

Base salary range: $225,000.00 – $250,000.00. Salary determinations are based on relevant work experience, skills, certifications, and location.

• Comprehensive medical, dental, and vision coverage.
• 401(k) with employer match and profit‑sharing contribution.
• Wellness incentive program.
• Life, accidental death, and dismemberment (AD&D) insurance.
• Flexible spending programs.
• Short‑term and long‑term disability plans.
• Paid time off program.
• Paid charitable leave.
• Paid parental leave.
• Tuition reimbursement program.
• Personal insurance (auto/homeowners) discounts.

EEO Statement

MSIG USA provides equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, sexual orientation, gender identity or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state or local law. MSIG USA will provide reasonable accommodations for qualified individuals with disabilities.