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Open nowFirst seen 5 days ago

Chief Analytics Officer (CAO) — Insurance & Investments

thehivecareers.co2,951 open roles

Where
San Juan, Puerto Rico, Remote
Work mode
Remote
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Your applicationOpen nowChief Analytics Officer (CAO) — Insurance & Investmentsthehivecareers.co · San Juan, Puerto Rico, Remote

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The clock on this job

Early applications get read.

12.3% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.3%7 days
  4. 19.3%14 days
  5. 35.6%30 days
  6. 58.1%60 days
This job: first seen 5 days ago

The posting

Job Summary

The Chief Analytics Officer (CAO) is the executive leader responsible for using enterprise data, advanced analytics, AI, and business intelligence to improve strategic and operational decision-making.

Within Insurance & Investments, the CAO typically oversees analytics across underwriting, claims, pricing, customer intelligence, fraud, risk, actuarial insights, investment performance, portfolio analytics, financial planning, regulatory reporting, and enterprise performance.

Key Responsibilities

Define and execute the organization's enterprise analytics strategy.

Establish an enterprise-wide analytics operating model, roadmap, standards, and priorities.

Lead advanced analytics, predictive analytics, AI/ML, data science, and business intelligence.

Translate complex data into actionable insights for CEO, Board, executives, and business leaders.

Develop analytics capabilities for:

Underwriting and risk selection

Claims and loss analysis

Pricing and profitability

Customer segmentation and retention

Fraud detection

Risk and capital analytics

Portfolio and investment performance

Asset allocation

Market and investment research

Financial forecasting

Regulatory and management reporting

Establish enterprise analytics KPIs and measurement frameworks.

Drive predictive modelling and scenario analysis to support strategic decisions.

Partner with the CIO/CDO/CTO on data architecture, data platforms, governance, integration, and technology modernization.

Ensure analytical models use reliable, governed, secure, and appropriately controlled data.

Develop self-service BI and executive dashboards.

Identify opportunities for AI and automation across business functions.

Establish model governance, validation, monitoring, and responsible AI practices.

Support actuarial, risk, finance, investment, compliance, and executive decision-making.

Lead enterprise analytics transformation and data-driven culture.

Build, manage, and develop high-performing teams across analytics, data science, BI, and AI.

Manage analytics budgets, vendors, strategic technology partners, and external data providers.

Communicate analytical findings and business implications to senior executives and the Board.

Ensure analytics activities align with regulatory, privacy, risk, and financial-services requirements.

Ideal Candidate Profile

15+ years of experience across analytics, data science, BI, statistics, quantitative analysis, or related fields.

7+ years in senior analytics/data leadership.

Previous experience as:

Chief Analytics Officer

Chief Data & Analytics Officer

Chief Data Officer

Head of Data & Analytics

Head of Analytics

Group Head of Analytics

Director of Data & Analytics

Analytics Director

VP Data & Analytics

Strong experience in Insurance, Banking, Investment Management, Asset Management, Wealth Management, or Financial Services.

Strong understanding of:

Advanced analytics

Predictive modelling

AI/ML

Data science

Business intelligence

Data strategy

Data governance

Data architecture

Statistical modelling

Data visualization

Scenario/stress testing

Experience converting analytics into measurable business outcomes.

Strong executive stakeholder management and Board-level communication.

Experience leading large, multidisciplinary analytics/data teams.

Strong commercial and strategic understanding of financial-services businesses.

Bachelor's degree required; Master's/PhD in Data Science, Statistics, Mathematics, Computer Science, Economics, Finance, Actuarial Science, or a related field is advantageous.

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