AVP Advanced Analytics

The AVP Advanced Analytics, Marketing Customer Experience & Distribution provides visionary leadership and strategic direction for the organization's data science initiatives, machine learning, modeling, driving innovation, and leveraging data-driven insights to achieve business objectives and competitive advantage. This role will have a marketing focus but will touch on all areas of insurance.

Key Skills:

Strategic Communication: Demonstrates exceptional strategic communication skills with an ability to articulate complex concepts to executive-level stakeholders.

Executive-Level Data Presentation: Ability to present data-driven insights and recommendations to executive leadership in a clear and compelling manner.

Advanced Data Analysis and Machine Learning: Mastery of strategic data analysis, machine learning techniques, and statistical model frameworks to solve complex business problems and drive organizational strategy and innovation.

Technical Data Mastery: Expert-level proficiency in working with data using query languages such as SQL, R, or Python, with a deep understanding of relational data and data tools (Git, github, snowflake, open source ecosystem etc).

Coding Expertise: Expertise in writing complex, efficient, and scalable production-ready code in Python or R. Knowledge of generative AI for coding is a plus.

BI Strategy: Ability to develop and execute a comprehensive BI strategy that aligns with organizational goals and objectives.

Visionary Leadership: Demonstrates visionary leadership in driving data-driven initiatives and fostering a culture of innovation and excellence.

Strategic Partnerships: Ability to build strategic partnerships both internally and externally to leverage data assets and drive business growth and transformation.

Manager skills: (if a manager) ability to coach/mentor/inspire other data scientists and non-technical people in the use of data science and analytics

Job Requirements:

• Preferred education/experience: OR Required education
• Master’s degree or higher in data science related areas (statistics, applied economics, data science)
• 8+ years of professional analytical experience (4 required)
• 8+ years of P&C or Life/Retirement experience (4 required)

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