We are looking for a talented Insurance Data Scientist for our Research and Risk team, a team that is at the core of everything we do. In this role, you will research, develop and improve pricing models and rate plans, using advanced modeling techniques, continuous experimentation, and an iterative approach to productizing our learnings. You will work closely with product management, underwriting, actuaries, machine learning engineers and other product/engineering teams.
A day in the life
Develop and refine predictive pricing and risk models using statistical and machine learning techniques to improve underwriting accuracy and pricing fairness
Evaluate existing rate structures and pricing methodologies, identifying opportunities to enhance predictive performance and business impact
Collaborate with actuarial and underwriting teams to ensure models align with regulatory and business requirements
Create POCs to validate new product ideas and experiments to improve existing predictive models
Design data collection strategies and their applications for building new products
A day in the life
Develop and refine predictive pricing and risk models using statistical and machine learning techniques to improve underwriting accuracy and pricing fairness
Evaluate existing rate structures and pricing methodologies, identifying opportunities to enhance predictive performance and business impact
Collaborate with actuarial and underwriting teams to ensure models align with regulatory and business requirements
Create POCs to validate new product ideas and experiments to improve existing predictive models
Design data collection strategies and their applications for building new products
Requirements:
MSc (or higher) in Statistics, Machine Learning, Applied Mathematics, or a related quantitative field.
4+ years of experience as a data scientist, with significant focus on insurance pricing or underwriting analytics.
Strong domain expertise in insurance pricing workflows, including rate plan development, evaluation, and optimization.
High proficiency in statistics, machine learning algorithms, data manipulation and analysis.
Extensive experience in research-oriented roles, analyzing business problems from a data science perspective, conducting literature research, and implementing and testing solutions.
Expertise in supervised and unsupervised machine learning models (e.g., GLM, GAM, XGBoost, Deep Learning).
A proactive approach to staying updated with the latest developments in AI and incorporating them to enhance existing products.
A product-driven mindset with a knack for transforming research outcomes into impactful products.
Excellent communication skills, with the ability to articulate experiment goals and methodologies clearly and communicate insights effectively to the team.
MSc (or higher) in Statistics, Machine Learning, Applied Mathematics, or a related quantitative field.
4+ years of experience as a data scientist, with significant focus on insurance pricing or underwriting analytics.
Strong domain expertise in insurance pricing workflows, including rate plan development, evaluation, and optimization.
High proficiency in statistics, machine learning algorithms, data manipulation and analysis.
Extensive experience in research-oriented roles, analyzing business problems from a data science perspective, conducting literature research, and implementing and testing solutions.
Expertise in supervised and unsupervised machine learning models (e.g., GLM, GAM, XGBoost, Deep Learning).
A proactive approach to staying updated with the latest developments in AI and incorporating them to enhance existing products.
A product-driven mindset with a knack for transforming research outcomes into impactful products.
Excellent communication skills, with the ability to articulate experiment goals and methodologies clearly and communicate insights effectively to the team.
This position is open to all candidates.
