Decision Science Analyst III

Hagerty

2d•Remote

About The Position

As a Decision Science Analyst III who is an analytically rigorous, business-curious analyst you will join our Customer Analytics team. You'll sit at the intersection of data science, product intelligence, and business strategy: mapping how customers discover, adopt, and stay with our subscription and property & casualty insurance products. Your work will shape retention strategy, pricing decisions, and personalized customer experiences across the full lifecycle. Emphasis placed on intellectual curiosity and honesty, willingness to experiment and cultivate relationships with contributors occupying different functional roles, strategic thought, communication skills and the ability to articulate complex relationships to business leaders. A background in subscription-based services or auto insurance a plus.

Requirements

BA degree in a quantitative field or at least five years’ experience in analytically rigorous data projects
Employed in P&C insurance, financial technology, or a subscription business
Experience applying analytics to business intelligence, customer journey /customer experience analytics and statistical model development.
Experience with SQL, Snowflake, dbt and Tableau are a must.

Nice To Haves

advanced degrees a plus
Experience with Python, SAS, SPSS, Stata or R are nice-to-haves.
Experience managing product feature adoption and product usage in multi-channel contexts is desirable.
Familiarity with public company requirements, including Sarbanes Oxley and key regulations, if applicable.

Responsibilities

Design and document data models using dbt in Snowflake that support business intelligence, analysis, model development and journey reporting at scale
Build and maintain Tableau dashboards tracking KPIs across acquisition, engagement, and retention
Contribute to identity resolution frameworks using customer data platforms
Establish data definitions and governance standards for customer-level metrics
Partner with data engineering to ensure analytical data assets are accurate and production-ready
Partner with data scientists to develop datasets in furtherance of statistical model development (eg: identification of dependent and candidate independent variables, exploratory analysis of relationships with increasing mathematical abstraction)
Map customer journeys across subscription and P&C insurance products
Build and maintain survival and churn analyses to quantify retention risk at each lifecycle stage, eg: time-to-event analysis or hazard estimates
Develop data resources for propensity models to support cross-sell, upsell, renewal, and lapse prediction
Conduct engagement analyses to identify and describe behavioral signals tied to conversion and retention
Design and evaluate A/B and multivariate tests across product, sales and marketing touchpoints
Support pricing analysis for subscription types and auto insurance products, quantifying elasticity of demand and competitive positioning
Analyze product feature adoption and product usage to inform roadmap prioritization. Experience managing these in multi-channel contexts is desirable.
Propose segmentations that explain differentiated product use patterns, price-taking behaviors and cohort-level retention/migration
Partner with product and strategy teams on risk-adjusted retention and LTV frameworks
Develop recommendation logic for next-best-action, next-best-product, and content personalization
Collaborate with customer journey and customer experience teams to operationalize segmentation and triggers in the Customer Data Platform
Measure lift and incrementality of personalization initiatives
Surface customer insights that inform omnichannel communication strategies