Senior Data Analyst - Insurance

As a Senior Data Analyst at Kinetic, your main responsibilities include building and managing dashboards to track progress against objectives, conducting deep-dive analyses to enhance insurance product performance, and identifying growth and profitability opportunities. You’ll work closely with various stakeholders in the insurance sector, ensuring that the company’s decisions are informed by insights drawn from comprehensive data analysis.

To qualify for the Senior Data Analyst position at Kinetic, you should have over 5 years of professional experience in a quantitative analysis role, preferably within commercial insurance. A BS/BA degree is required, alongside a strong understanding of statistical metrics and proficiency in data analysis tools like SQL and programming languages like Python. Familiarity with dashboarding tools such as Tableau or Looker is also essential.

A Senior Data Analyst at Kinetic should be proficient in database query tools such as SQL and comfortable with spreadsheet tools like Excel or Google Sheets. Knowledge of data visualization tools such as Tableau, Mixpanel, or Looker is crucial for building clear dashboards. Familiarity with data science programming languages, especially Python, is a significant advantage.

Kinetic defines success for the Senior Data Analyst role through the ability to uncover meaningful insights from complex data sets that guide strategic business decisions. Success is measured by the quality and clarity of the dashboards you create and how effectively those analytics influence decision-making across the company to drive growth and profitability.

As a Senior Data Analyst at Kinetic, you'll find numerous growth opportunities, including the potential to influence product strategy through your analyses. Additionally, Kinetic encourages continuous learning and adaptation, particularly in AI and data science, allowing you to evolve your skills while contributing to the company’s rapid growth and impact in the insurance industry.

In answering this question, focus on specific projects where you've utilized data visualization tools like Tableau or Looker. Describe how you used these tools to present complex data in a clear, actionable format that guided business decisions.

When tackling this question, outline your systematic approach: defining the problem, gathering relevant data, conducting your analysis, and finally deriving actionable insights. Emphasize your analytical thinking and the iterative process of refining your methods based on findings.

Address this question by mentioning key statistical methods, such as regression analysis, hypothesis testing, and variance analysis. Provide examples of how you’ve successfully applied these methods in past roles to generate insights and guide decisions.

Share a specific example where your data analysis led to significant changes or strategies within your company. Highlight the metrics involved, the methods used, and the positive outcomes resulting from your insights.

Discuss your strategies for maintaining data accuracy, such as cross-referencing sources, leveraging data validation techniques, and creating rigorous testing processes. These methods not only ensure reliability but also build trust in your analytical outputs.

In your answer, describe how you assess project urgencies versus strategic importance. Explain your time management strategies – such as using prioritization frameworks or communication with stakeholders – to ensure that you meet both deadlines and business needs.

Provide examples of how you’ve collaborated with different departments, such as product, underwriting, or claims. Highlight your role in communicating findings to mixed-skill audiences and how your insights facilitated common goals.

Share your passion for uncovering insights through data and how you enjoy solving complex problems. Talk about your excitement in seeing how data-driven decisions can lead to tangible improvements within an organization, especially in enhancing safety and efficiency.

Mention your commitment to professional development through attending webinars, following relevant publications, and networking with industry professionals. This shows that you are proactive not only about your role but also about the broader industry context.

Outline a structured plan that includes familiarizing yourself with existing data systems, meeting with key stakeholders, and identifying urgent analytical needs based on Kinetic’s current goals. This demonstrates initiative and a clear understanding of the importance of data alignment with business strategy.