Director Data Science

As the Director of Data Science at Kemper, your primary responsibilities include leading a talented team of data scientists and engineers, developing analytical capabilities to address various business needs, and collaborating with cross-functional teams to leverage data science solutions effectively. You will also be responsible for presenting insights to senior leadership, overseeing model governance processes, and mentoring junior staff.

To qualify for the Director of Data Science role at Kemper, candidates should possess a graduate degree in Mathematics, Engineering, or a related STEM field, along with at least 10 years of experience in the insurance industry or a related data science environment. A PhD is preferred, and robust experience in statistical modeling and AI/ML platforms is essential.

A Director of Data Science can drive significant competitive advantage for Kemper by harnessing data to solve complex business problems, developing innovative analytical strategies, and mentoring a high-performing analytic team. This leadership position is pivotal in ensuring that data science initiatives are effectively integrated with business objectives, thus delivering real value to our stakeholders.

The Director of Data Science at Kemper will oversee a diverse team comprised of data scientists and data engineers. This role involves fostering collaboration within the team and with other business areas, guiding team members through projects, and ensuring alignment between analytics and business goals.

At Kemper, the Director of Data Science will oversee a variety of projects aimed at solving business challenges through advanced analytical techniques. This includes developing statistical models, implementing machine learning algorithms, and creating insights that can help inform strategic business decisions.

When answering this question, share specific examples of how you've led data science initiatives, fostered a collaborative team environment, and mentored junior analysts. Focus on your leadership style and any achievements that highlight your ability to build high-performing teams.

Discuss the statistical modeling techniques you've used in previous roles, such as regression, classification, clustering, etc. Be ready to provide examples of how you've applied these techniques to solve business problems and the outcomes of those projects.

To answer this question effectively, describe your approach to model governance, including how you document, test, and validate models throughout their lifecycle. Mention any frameworks or processes you’ve implemented to maintain model integrity and compliance with business standards.

Provide an example of how you've successfully communicated complex data findings to senior leadership. Explain the context, your preparation process, and how you tailored your message to ensure the insights were understood and actionable for decision-making.

Discuss your belief in mentoring as a means to develop talent within your team. Share experiences where you've successfully coached team members, the impact it had on their careers, and how it contributed to overall team performance.

Mention resources you rely on, such as industry publications, webinars, conferences, and online courses. Highlight your commitment to continuous learning and how you encourage your team to also embrace new developments in the data science field.

Be honest and strategic in discussing challenges you’ve encountered, such as data quality issues or team dynamics. Explain the steps you took to resolve these challenges and the lessons learned, demonstrating your problem-solving skills.

Explain your approach to project prioritization based on business needs, resource availability, and potential impact. Discuss any frameworks or methodologies you use to evaluate and prioritize projects effectively.

Reflect on how you adapt your communication style based on your audience. Emphasize the importance of clarity and engagement, particularly when explaining complex analytical concepts to non-technical stakeholders.

Express your admiration for Kemper’s commitment to innovation and the role that data science plays in its strategy. Mention how your values align with Kemper's mission and why you are excited about the opportunity to lead a talented team in making data-driven decisions.