Sr. Principal Analyst – Data Analytics & AI in Insurance and Financial Services (Remote US)

About the role:

Gartner Analysts are industry thought leaders who create must-have research, market predictions and best practices for a broad range of world-leading organizations. A Sr Principal Analyst possesses a keen eye for identifying gaps, problems, and solutions within their market. They use their knowledge to help clients make better decisions, solve complex issues and execute new practices that propel clients’ businesses toward critical objectives. An Analyst publishes these insights as pragmatic and provocative research. Additionally, they reinforce Gartner’s value every day by engaging clients via in-person and virtual meetings, sales support visits, Gartner conferences and industry events. This includes writing about, presenting and advising financial services and insurance organizations about market trends, vendors, services, governance and best practices in Data & Analytics and AI. 

What you will do:

• Create high-quality, clear, actionable, “must-have research” content based on research best practices and methodologies in financial services in the topic of data and analytics, AI and data science. Specific focus areas will include strategy, business value, best practices, market trends, technologies and vendors of our target audience including CIOs and product leaders at vendors.

• Broad spectrum coverage of the market, and produce innovative, thought-leading, impactful, analytically deep, fact-based research.

• Serve as a leading authority on insurance AI and advanced analytics topics, such as: understanding insurance and financial services AI use cases; setting up AI pilots and scaling AI initiatives; ensuring proper governance of AI tools; navigating the AI technology landscape; connecting AI to day-to-day process improvement and wholesale transformation.

• Stay abreast of broader research and trends in artificial intelligence and data analytics methods with application in insurance and financial services.

• Provide current and prospective clients with actionable advice via virtual and face-to-face interactions.

• Support business growth and client engagement strategies by partnering with Gartner’s commercial organization to create long-term value for both clients and Gartner.

• Provide clients and prospects with actionable analytics & AI-centric advice via virtual or face-to-face interactions.

• Act as an internal advisor on how data and analytics and AI practices, technologies and approaches are impacting the insurance function.

• Create and deliver presentation materials for Gartner events, industry and professional association conferences, and client briefings.

• Build your personal brand as a functional expert to drive Gartner’s research, methodology and strategy.

• Provide high-quality and timely research peer review.  Provide mentorship and support to team members.

• Actively participate in innovation, ideation, and research discussions and collaborate effectively with peers in the analytics & AI research community.

What you will need:

• Bachelor's degree or equivalent experience; Graduate degree preferred.

• 8-10 years’ of experience with insurance services AI topics or working in D&A on AI related topics.

• Relative insurance experience with increasing scope and responsibility in one or more lines of business such as property and casualty, and life and annuities. Also, wealth management and investment services within the insurance context.

• Experience with the deployment of advanced analytics capabilities to support short-, mid- or long-term decision making in one or more functions such as actuarial science, underwriting, claims/billing, operations, call center, insurance asset management, etc.

• Ability to work in a small team setting.  Self-starter with the ability to successfully navigate through a matrixed organization.

• Strong written and verbal proficiency, analytical and presentation skills; ability to engage clients and respond effectively to questions.

• Exposure to advanced analytics tools and approaches via on-the-job experience or formalized education (backgrounds in math, statistics, and physics a plus).

• Exposure to using AI/ML in forecasting, or experience with quantitative analytics, statistics and coding languages (preferably Python) a bonus.

• Moderate willin