Manager, Data & Analytics

Incline P&C Group•Austin, TX

9d•Hybrid

About The Position

Incline Insurance Group is seeking a Manager, Data & Analytics to lead its enterprise reporting and analytics function. The role shapes how data is governed, integrated, analyzed, and used to support business decisions across underwriting, actuarial, finance, reinsurance, and operations. The leader sets direction for enterprise data quality, reporting, and analytics while staying connected to the technical and operational needs of a growing property and casualty program insurer. They partner with business and technology leaders to strengthen the enterprise data warehouse, support major system implementations, and deliver reliable, decision-ready insights. The Manager develops the enterprise data and analytics roadmap; oversees integration of insurance and partner data; establishes governance and quality practices; and partners with IT and engineering on data architecture and platforms. They lead trusted reporting and business insights, identify automation and advanced analytics opportunities, represent the function in enterprise transformations, advise cross-functional leaders, and lead the data and analytics team and relevant external partners.

Requirements

At least 6 years of progressive experience in enterprise data, analytics, business intelligence, or data operations.
Experience leading teams, programs, or major cross-functional initiatives.
Strong command of SQL, data modeling, ETL/ELT, enterprise data warehousing, and analytics platforms.
Experience with Snowflake, cloud data environments (AWS preferred), and reporting tools such as Power BI or QuickSight.
Familiarity with Python, dbt, Matillion, or comparable technologies; automation, API integrations, and end-to-end data flows.
Understanding of policy, premium, claims, billing, and reinsurance datasets, and the relationship between data controls, reporting, and financial and operational outcomes.
Hands-on understanding of bordereaux data and premium and loss reporting; understanding of data transformations and validations for data quality in downstream systems and reporting.
Demonstrated ability to set priorities, influence senior stakeholders, develop talent, manage competing demands, and deliver measurable improvements in data quality, reporting reliability, and business decision-making.
Bachelor’s degree in Data Science, Computer Science, Information Systems, Mathematics, Statistics, Finance, or a related field.

Nice To Haves

Insurance industry experience is strongly preferred; P&C program, fronting, MGA, or reinsurance exposure is particularly valuable.
Advanced degree preferred.
Familiarity with Duck Creek, Workday, Salesforce, or regulatory reporting.
Experience supporting enterprise system implementations, data governance programs, automation initiatives, and applied AI/ML or advanced analytics in a regulated environment.

Responsibilities

Develop and execute the enterprise data and analytics roadmap, prioritizing initiatives by business value, data integrity, scalability, and regulatory needs; establish reporting standards and an operating model.
Oversee ingestion, transformation, and standardization of premium, claims, billing, endorsements, policy lifecycle, and MGA-sourced data, including integration across Duck Creek Reinsurance, Workday, Salesforce, Snowflake, and related systems.
Establish ownership, definitions, controls, documentation, and monitoring for critical enterprise data; direct resolution of complex reconciliations and discrepancies across data platforms and financial and operational reporting.
Partner with IT and engineering on Snowflake data models, SQL transformation logic, pipeline design, warehouse performance, scalable architecture, and data-management practices.
Lead development of executive dashboards, KPIs, and reporting solutions using Power BI, QuickSight, or comparable tools; support analysis of underwriting results, claims trends, portfolio profitability, reinsurance performance, and financial outcomes.
Identify opportunities to automate manual reconciliations and reporting using SQL, Python, and modern data tools; evaluate predictive analytics, anomaly detection, and AI-enabled use cases with appropriate governance and practical business value.
Represent the data and analytics function in enterprise implementations, including requirements, mapping, testing, migration, and adoption; ensure reliable downstream reporting and controls.
Advise Finance, Actuarial, Underwriting, Reinsurance, Operations, and IT leaders; translate business questions into analytics priorities and communicate technical findings in clear business terms.
Lead, coach, and develop data and analytics professionals; set priorities, delivery standards, and accountability; manage relevant external partners and resources.
Define and maintain data standards, templates, and mapping layers for premium, loss, and exposure bordereaux across MGAs and program partners; design repeatable partner onboarding processes, including data requirements, testing, and go-live criteria.