Data Analyst

Responsibilities

Data Preparation and Cleaning

• Work with large datasets from multiple sources, performing data cleaning, preparation, and transformation as needed.
• Automate data preparation processes to improve efficiency and scalability.
• Develop and maintain a business-friendly data catalog with detailed descriptions, support self-service analytics platforms, and ensure data quality and governance practices are followed to enhance data accessibility and reliability.

Data Visualization

• Develop and maintain dashboards and reports to support strategic decision-making and track key performance metrics using tools like Tableau, Metabase, or Excel.

Data Analysis and Insight Generation

• Analyze data trends and ensure accuracy and relevancy to address business questions or problems.
• Identify actionable insights and recommend solutions that align with company objectives and drive measurable impact.
• Research publicly available resources (e.g., journal articles, white papers) to enhance analysis quality and provide well-informed recommendations.

Reporting

• Prepare accurate, concise, and meaningful reports that describe and interpret analysis findings to support decision-making by upper management.
• Respond to and fulfill ad hoc data requests promptly, ensuring accuracy and relevance to support business needs.
• Collaborate with stakeholders to clarify reporting requirements and ensure deliverables align with expectations.

Your Profile

• Proficiency in SQL and working with data warehousing platforms like AWS Redshift and Databricks.
• Experience with data transformation tools like dbt.
• Experience with data visualization tools like Tableau or Metabase and a keen interest in improving user experience on self-service platforms.
• Advanced proficiency in MS Excel, including Pivot Tables and Macros.
• Optional programming skills in Python.
• Strong critical thinking and problem-solving skills with a focus on root cause analysis and effective follow-through.
• Ability to analyze information, evaluate results, and implement the best solutions to solve problems efficiently.
• Strong attention to detail and accuracy, with the ability to produce quality work under tight deadlines.
• Ability to manage and prioritize multiple projects with varying deadlines and shift efficiently between competing priorities.
• Understanding of data governance and data management principles, with an emphasis on data quality and accuracy.
• Excellent communication skills to collaborate with cross-functional teams and explain technical concepts to non-technical audiences.
• Interest in working with data within the insurance industry and learning mapping or related software.