Sr. Data Scientist

PURE Insurance

2d • $120,000 - $145,000 • Onsite

About The Position

At PURE Insurance, data science is more than just algorithms and models - it’s a core part of how we solve problems, guide decisions, and deliver value to our members. Our team works across the entire business - from underwriting and claims to marketing, finance, and risk management - designing and implementing data-driven solutions that improve operations, support strategic goals, and ultimately serve our membership with excellence and care. We are hiring a Senior Data Scientist to join our growing team. This hands-on, high-impact role offers the opportunity to collaborate across departments, work with a modern data stack, and contribute directly to initiatives that influence key decisions and outcomes across the company.

Requirements

• 3 to 5 years of experience in data science, applying statistical and machine learning techniques to solve business problems.
• At least 2 years of experience working in the Property & Casualty (P&C) insurance industry.
• Proficient in Python (pandas, NumPy, scikit-learn, and others) for data science and machine learning.
• Proficient in SQL for data querying and management.
• Strong working experience with Git and version control workflows in a collaborative environment.
• Familiarity with tools for data visualization (e.g., matplotlib, seaborn, Plotly), and experience communicating findings through dashboards or reporting tools.
• Experience querying large databases and transforming raw data into structured modeling-ready datasets.
• A collaborative mindset with the ability to take ownership and work independently in a fast-paced, cross-functional setting.
• A Bachelor's degree or higher in a quantitative field such as Data Science, Computer Science, Engineering, Statistics, or Applied Mathematics.

Nice To Haves

• Comfort working with modern ML/AI libraries and techniques; exposure to natural language processing, geospatial data, or unstructured data (e.g., text, image, audio) is a plus.

Responsibilities

• Analyze large and complex datasets to uncover patterns, generate insights, and support strategic decision-making.
• Build predictive models and machine learning algorithms to address a wide range of business problems.
• Create scalable data pipelines and streamline processes through automation.
• Collaborate with cross-functional teams including underwriting, claims, risk, actuarial, and marketing to understand needs and deliver data science solutions that matter.
• Communicate results and recommendations clearly to both technical and non-technical stakeholders through presentations, visualizations, and written reports.
• Develop high-quality modeling datasets by integrating internal and third-party data sources.
• Monitor deployed models and continuously improve performance through evaluation, tuning, and retraining.
• Work with a modern tech stack that includes Python, SQL, Databricks, dbt, GitHub, Hex, Arize, and other contemporary platforms and tools.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level