Demand modeling: Develop and apply predictive models to estimate the probability of policy conversion.
Market modeling: Develop and apply predictive models to estimate key rates in the insurance market.
Data analysis: Perform detailed statistical analyses and process large volumes of data to extract insights that support pricing decisions.
Support to the Pricing team: Provide data-driven information and recommendations to guide product pricing, adjusting rates and parameters to improve competitiveness and profitability.
Performance monitoring: Track model performance and evaluate the appropriate timing for adjustments or updates.
Rate and elasticity models: Apply price elasticity models and assess consumer sensitivity to changes in insurance premiums.
Report and presentation creation: Prepare detailed reports and presentations on demand modeling results for executive and product teams.
Model implementation: Translate models into implementable formats for deployment in operational tools and convert models into production-ready code.
Variable clustering: Develop groupings of strategic variables using clustering techniques to bring parsimony to models and processes.
Machine Learning techniques: Use advanced machine learning methods to obtain the best estimates for our models.
Requirements
Degree in Actuarial Science, Statistics, Mathematics, Computer Science, Economics, or a related field.
Experience in the insurance or finance sector.
Experience applying analytical techniques and predictive modeling.
Advanced proficiency in at least one data-science programming language (Python, R, SQL, SAS, etc.) and a commitment to continuous learning.
Proficiency in querying and manipulating databases for model building, validation, and monitoring.
Knowledge of Earnix, Emblem, AWS/SageMaker, or similar tools.
Communication skills to present complex results clearly and persuasively.
Analytical mindset, strong attention to detail, and the ability to work autonomously in a dynamic environment.
Experience collaborating with cross-functional teams and the aptitude to develop strong interpersonal relationships.
Ability to lead projects and maintain a broad view of the entire pricing mechanism.
Support the technical development of junior analysts and data scientists by promoting knowledge sharing, conducting code reviews, and organizing learning sessions.