This position is not eligible for employment visa sponsorship. Applicants must be authorized to work in the United States without the need for current or future sponsorship.
Essential Job Functions And Responsibilities
- Assists in analyzing large, complex datasets to identify trends, patterns, and opportunities.
- Designs, develops, and deploys predictive models for underwriting, pricing, claims, and customer retention.
- Assists with designing and implementing data pipelines and automated reporting tools.
- Participates in collaborating with actuarial, underwriting, claims, and product teams to translate business problems into data science solutions.
- Assists with communicating data insights and recommendations to leadership through compelling data storytelling and visualization.
- Monitors and maintains model performance and ensures data quality and integrity.
- Participates in driving innovation by exploring new data sources, modeling techniques, and technologies to enhance business performance.
- Participates in collaborating with data engineers to ensure data quality, accessibility, and scalability.
- Performs other duties as assigned.
Job Requirements
Education: Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, Actuarial Science , or a related quantitative field or equivalent work experience is required. PhD preferred.
Experience: No prior work experience is required.
Scope of Job/Qualifications:
- Proficient in techniques for optimizing models, machine learning, and in analytical programming languages.
- Proficiency in Python, SQL, and machine learning libraries (e.g., scikit-learn, XGBoost, LightGBM).
- Familiarity with cloud platforms (AWS, Azure, or GCP) and data pipeline tools (e.g., Airflow, dbt).
- Familiar with geospatial data, telematics, or catastrophe modeling.
- Proficiency in data visualization tools (e.g., Tableau, Power BI) and dashboard development.
- Develops and maintains an understanding of the organization's business and technology operations.
- Developing knowledge of department policies and procedures.
- Developing knowledge of industry trends and technologies to continuously improve data modeling and insights as well as knowledge of regulatory requirements and model governance in insurance.
