Chief Data Officer

SGI; New York (NY); On-site; USD 250,000 - 450,000; Full time

Job summary

SGI is seeking a senior leader to own data science and pricing within its new MGA backed by a leading private equity investor. You will report to the CEO and build the function, team and platforms turning data into underwriting advantage.

You will set pricing strategy, lead predictive modelling, and design a cloud-based data platform from scratch, guiding AI/automation in production underwriting workflows and delivering portfolio insights to executives and partners.

Qualifications

• Senior leadership experience in pricing, data science or analytics within insurance environments.
• A strong technical grounding in pricing and predictive modelling; actuarial qualification or advanced quantitative degree is highly regarded.
• A proven track record building data and analytics capability, ideally with a modern cloud data platform.
• Experience taking machine learning and AI from development into production with measurable underwriting results.
• Commercially minded and comfortable working with underwriters, CEO, investors and partners.
• A builder who thrives in a start-up or scale-up setting and shaping a function from the ground up.

Responsibilities

• Set the data, analytics and pricing strategy aligned with the plan and investor goals.
• Lead pricing across the portfolio including rating models, rate adequacy and governance.
• Build and lead the data science team for predictive models for risk, pricing and portfolio management.
• Design and deliver a modern data platform covering data architecture and data governance.
• Deploy AI/ML in production underwriting workflows with evaluation and oversight.
• Provide timely, trusted portfolio performance information to CEO, board and partners.
• Support capacity partners with data, pricing evidence and reporting.
• Hire and develop pricing actuaries, data scientists and data engineers.

Skills

Senior leadership

Pricing strategy

Data science

Analytics

Stakeholder management

Education

FCAS/ACAS or equivalent

Tools

Cloud data platform

ML production

Job description

Our client is a new MGA backed by a leading private equity investor, built from the ground up to compete on data. With strong capital support, experienced underwriting leadership and a clear growth plan, the business has an unusual chance to design its data, analytics and pricing capability from day one, with no legacy to unwind.

The opportunity

This is a rare chance to own both data science and pricing. In most insurers and MGAs, pricing sits separately within actuarial or underwriting. Here, pricing, data science and data engineering all report to the Chief Data Officer, giving one leader end-to-end accountability for how the business uses data to select, price and grow profitably.

Reporting to the CEO and working closely with the investor and the board, you will build the function, the team and the platforms that turn data into underwriting advantage.

Key responsibilities

• Strategy: set the data, analytics and pricing strategy, aligned with the business plan and the investor’s value-creation goals.
• Pricing: lead pricing across the portfolio, including rating models, rate adequacy, rate filings where required, and pricing governance, working closely with underwriting leadership.
• Data science: build and lead the data science team, developing predictive models for risk selection, pricing, portfolio management and claims.
• Data platform: design and deliver a modern data platform from scratch, covering data architecture, ingestion of submission, bordereaux and third-party data, data quality and governance.
• AI and automation: put AI and machine learning into production underwriting workflows, with clear evaluation, monitoring and human oversight.
• Portfolio insight: give the CEO, underwriters, capacity partners and the board timely, trusted performance information, including loss ratio, rate monitoring and portfolio mix.
• Capacity partners: support carrier, reinsurance and fronting relationships with the data, pricing evidence and reporting that partners expect.
• Team building: hire and develop a high-performing team of pricing actuaries, data scientists and data engineers.

About you

• Senior leadership experience in pricing, data science or analytics within insurance, ideally specialty, commercial or MGA environments.
• A strong technical grounding in pricing and predictive modelling. An actuarial qualification (FCAS, ACAS or equivalent) or an advanced quantitative degree is highly regarded.
• A record of building data and analytics capability, ideally including a modern cloud data platform.
• Experience taking machine learning and AI from development into production with measurable underwriting results.
• Commercially minded and comfortable working with underwriters, the CEO, investors and capacity partners.
• A builder who thrives in a start-up or scale-up setting and wants to shape a function from the ground up.