Proven track record in the property and casualty insurance industry, with understanding of insurance products, underwriting processes, and market dynamics
Strong SQL skills
Proficiency in data analysis and visualization tools such as Python, Tableau, Power BI, Informatica, etc.
Requirements:
Apply in-depth knowledge of the property and casualty insurance industry to identify relevant data sources, extract pertinent information, and compile datasets for analysis.
Apply advanced data mining techniques to uncover patterns, trends, and correlations within large and sophisticated datasets, contributing to the development of predictive models and risk assessment strategies.
Collaborate with internal stakeholders to define data requirements, ensuring alignment with business objectives and providing guidance on data collection and quality enhancement.
Prepare and present clear, concise, and practical reports, dashboards, and presentations to communicate findings, recommendations, and insights to non-technical collaborators.
Job description
Data Analyst Contract Remote
U.S. Citizens and those authorized to work in the U.S. are encouraged to apply. We are unable to sponsor currently Job description:
As a Data Analyst specializing in the property and casualty insurance industry, you will play a pivotal role in extracting, analyzing, and interpreting data to uncover concrete insights that drive strategic business decisions. Applying your expertise in data mining, mapping, and analytics, you will collaborate closely with multi-functional teams to enhance our understanding of customer behavior, risk assessment, and market trends. Your ability to communicate complex findings in a clear and concise manner, as well as drive data-focused discussions, will be essential in crafting our data-driven initiatives.
Key Responsibilities:
Apply your in-depth knowledge of the property and casualty insurance industry to identify relevant data sources, extract pertinent information, and compile datasets for analysis.
Apply advanced data mining techniques to uncover patterns, trends, and correlations within large and sophisticated datasets, contributing to the development of predictive models and risk assessment strategies.
Collaborate with internal stakeholders to define data requirements, ensuring alignment with business objectives and providing guidance on data collection and quality enhancement.
Employ data mapping and visualization tools to transform raw data into easily interpretable visual representations, facilitating insights and decision-making processes.
Act as a proactive participant in data-related discussions, contributing your industry expertise to shape data strategies and solutions that address business challenges.
Prepare and present clear, concise, and practical reports, dashboards, and presentations to communicate findings, recommendations, and insights to non-technical collaborators.
Continuously monitor data accuracy, consistency, and completeness, identifying and addressing any anomalies or discrepancies to maintain data integrity.
Collaborate with data engineers and other technical teams to find opportunities for process automation, data pipeline improvements, and data quality enhancements.
Stay up-to-date with industry trends, standard methodologies, and new technologies in data analysis, insurance, and related domains.
Qualifications:
5+ years of experience as a data analyst.
Proven track record in the property and casualty insurance industry, with a solid understanding of insurance products, underwriting processes, and market dynamics.
Strong SQL skills
Proficiency in data analysis and visualization tools such as Python, Tableau, Power BI, Informatica, etc.
Demonstrated expertise in data mining, mapping, and analytical techniques to derive meaningful insights from complex datasets.
Exceptional communication skills, with the ability to convey technical findings to non-technical audiences and facilitate data-driven discussions.
Proven track record of driving data-focused initiatives, collaborating across teams to deliver impactful solutions.
Strong problem-solving skills and a keen attention to detail, ensuring accuracy and reliability of analytical results.
Expertise in SDLC full project life cycle
Ability to work independently and as part of a team in a fast-paced, dynamic environment.
