Insurance Service Line Sales Specialist

What you'll do

• Drive business growth through consultative selling of data, analytics, and AI capabilities.
• Identify opportunities to cross-sell and up-sell data and AI offerings to key stakeholders.
• Manage and ensure the profitable growth of your assigned portfolio.
• Partner with the network to develop and execute joint go-to-market strategies.
• Provide technical solutions to business problems using Azure, AWS, GCP, Snowflake, and Databricks.
• Execute large-scale consulting and program engagements within the data analytics and AI space.
• Communicate and influence business stakeholders up to the C-Suite level.
• Advise clients on data migration, governance, and modern data architecture.

What we're looking for

• Minimum 5 years of experience selling Data & Analytics solutions and services.
• Bachelor’s degree in engineering or equivalent.
• Experience in business growth or sales roles for data management, analytics, and AI, preferably in the Insurance domain.
• Experience with data migration, data management, governance, analytics, and reporting.
• Strong exposure to selling Data solutions on Azure, AWS, and GCP platforms and AI offerings.
• Sound knowledge of Snowflake, Databricks, Informatica, and other leading Data Products.
• Practitioners’ knowledge of Agentic AI, GenAI, and ML.
• Experience with leading visualization tools such as Power BI, Tableau, and Qlik.
• Experience with large-scale consulting and program execution engagements in the data analytics and AI space.
• Excellent ability to influence, communicate, and present to business stakeholders up to the C-Suite.
• Consultative selling experience is a must.
• MBA or master’s degree from a top-ranked institution (preferred).
• Certification and knowledge of AI trends and Agentic solutions, preferably in Banking, Insurance, or Healthcare (preferred).
• Knowledge of enterprise data management architecture, master data management, data governance, and data quality (preferred).
• Knowledge of data modernization, Cloud, data migration, and digital transformation (preferred).