The company is seeking to drive strategic decision-making, optimize marketing effectiveness, and elevate customer lifetime value in a highly competitive and evolving insurance landscape.
Requirements
- Current and extensive model development in Python or PySpark
- Possess current work experience in statistical modeling and analysis
- Works across coding languages used in Data Science (e.g. Python, SQL, and R)
- Knowledge of machine learning models, with a preference for experience in Natural Language Processing (NLP) or Large Language Models (LLMs)
Responsibilities
- Designing and executing data-driven solutions to quantify the performance of acquisition and retention efforts
- Developing, deploying, and maintaining models (e.g., propensity, churn, response, uplift) using techniques such as logistic regression, random forest, XGBoost, and clustering methods
- Working with structured and unstructured data from various sources (internal and external), ensuring quality, consistency, and readiness for modeling and analytics
- Designing tests and interpret results to guide marketing strategies, product changes, and retention interventions
- Communicating complex analyses and insights to technical and non-technical audiences
- Building dashboards and presentations that drive decision-making and transparency
Other
- Partnering closely with marketing, product, data engineering, and vertical business stakeholders to define requirements, align on business goals, and translate insights into actionable outcomes
- Health Benefits: Comprehensive, multi-carrier program for medical, dental and vision benefits
- Retirement Benefits: 401(k) with match and an Employee Share Purchase Plan
- Wellbeing: Wellness platform with incentives, Headspace app subscription, Employee Assistance and Time-off Programs
