Mercury Insurance is looking to enable the company to be data-driven through analyzing customer behavior, identifying performance trends, and driving continuous improvements to enhance digital experiences.
Requirements
- Proficiency in SQL and Python for data analysis and building data pipelines.
- Strong experience with data visualization tools (PowerBI) to create and maintain comprehensive dashboards.
- Expertise in relational and non-relational databases and data sources.
- Deep understanding of ETL/ELT processes and tools (e.g., dbt).
- Advanced data skills with the ability to work with large structured and unstructured data sets.
- Ability to identify gaps and inconsistencies in data, providing actionable insights.
- Solid experience with cloud-based advanced data and analytics environments.
Responsibilities
- Analyze User Behavior: Use SQL and Python to track, visualize, and analyze user engagement, focusing on multi-raters, aggregators, agents, and customer behaviors in the sales funnel.
- Improve User Experience (UX): Use data insights to drive product usability improvements, ensuring an intuitive and seamless user experience.
- Support Product Roadmap: Collaborate with product teams to integrate user behavior data into the product roadmap, aligning with key business objectives.
- Data Collection & Insights: Ensure that accurate data collection practices are followed and provide actionable insights into user behavior and product performance.
- Dashboard Development: Build and maintain dynamic sales funnel dashboards (using PowerBI), providing real-time insights into lead progression, conversion rates, and KPIs.
- Anomaly Detection: Implement and manage anomaly detection systems to proactively identify potential issues in user behavior or system performance.
- Technical Expertise: Apply strong knowledge of SQL, Python, and data visualization to solve complex product and UX challenges.
Other
- Bachelor’s degree in computer science, Mathematics, Statistics, Data Science, Business Analytics, or a related field.
- 5+ years of experience in data analytics, analytics engineering, data engineering, or data science.
- 4+ years of experience in product analytics, focusing on user behavior, engagement metrics, and product performance analysis.
- Strong written and verbal communication skills, capable of effectively conveying complex information.
- Ability to interact and collaborate with senior management and cross-functional teams.
