Python Engineer Manager

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Kemper is one of the nation’s leading specialized insurers. Our success is a direct reflection of the talented and diverse people who make a positive difference in the lives of our customers every day. We believe a high-performing culture, valuable opportunities for personal development and professional challenge, and a healthy work-life balance can be highly motivating and productive. Kemper’s products and services are making a real difference to our customers, who have unique and evolving needs. By joining our team, you are helping to provide an experience to our stakeholders that delivers on our promises. 

Position Summary:

Kemper Auto is seeking a highly skilled Resident Actuarial Engineer Manager to integrate solution development and data engineering practices within actuarial processes. This role bridges actuarial science, solution development, and advanced data engineering, ensuring data-driven decision-making is enabled through an ecosystem of capabilities built in seamless collaboration with the actuarial team. The ideal candidate will oversee the development, maintenance, and implementation of data-driven pricing strategies for personal and commercial auto insurance products, ensuring the accurate, actionable use of data to drive our business forward.

Position Responsibilities:

• Leadership: Lead a team of engineers, fostering a culture of innovation, collaboration and professional growth while delivery of high-quality analyses. Oversee the development of scalable data solutions, ensuring data accuracy, availability, and integrity, and implement cloud-based strategies tailored to actuarial needs.
• Actuarial Solution Development: Develop and maintain a suite of actuarial capabilities, inclusive of processes for portfolio re-rating to better understand the impact of proposed changes and expected performance. Develop solutions using Python in a cloud-based ecosystem.
• Actuarial Data Support: Collaborate with the actuarial team to provide solutions for pricing through advanced analytics and automation tools, ensuring alignment with actuarial methodologies and business requirements. Work closely with data solutions teams to ensure that data is structured for consumption by the actuarial team and that actuarial data requirements are fully articulated. Ensures that data is ingested into the actuarial ecosystem in a governed and controlled fashion. 
• Innovation and Optimization: Drive advanced analytics adoption to improve actuarial processes, optimize data workflows, identify and resolve inefficiencies in current operations to enhance team productivity.  Develop scalable programming solutions, and implement data strategies that align with organizational objectives and key performance indicators (KPIs). Automate and streamline processes to improve efficiency and accuracy.
• Data Governance & Compliance: Establish and enforce data governance protocols to ensure compliance with regulatory standards, safeguard data security and maintain accuracy and integrity by adhering to industry and actuarial best practices.
• Collaboration: Work closely with the actuarial team to align data and pricing strategies with business objectives.  Recognizing potential system opportunities or issues during data analysis and communicating them to business technology partners as needed. Provide training and support to team members and stakeholders to understanding and adoption of pricing technologies.

Position Qualifications:

• Bachelor’s degree in Computer Science, Data Engineering, Data Analytics or a related field.
• 5+ years of experience in solution or data engineering, data analysis or a similar role Proven experience in managing technical team and mentoring.
• 3+ years experience in Python development, with experience creating python-based applications utilizing clean code techniques.
• SAS proficiency is a plus
• Test-driven development experience is a plus
• Experience with Amazon SageMaker is a plus
• Knowledge of  data manipulation techniques and data ingestion patterns.
• Experience with cloud platforms (e.g., AWS, Azure, Google Cloud)
• Proficiency working with data visualization tools such as Tableau and Power BI. 
• Experience working in an actuarial or research field in a data engineering role supporting advanced analytics
• Familiarity with actuarial principles, insurance data structures, regulatory requirements and reporting standards.
• Strong analytical problem-solving and critical thinking skills with a results-oriented mindset.
• Excellent written and verbal communication skills with ability to translate business needs into technical solutions.
• Proven track record of delivering large-scale data-driven projects.

The range for this position is $99,000 to $164,800. When determining candidate offers, we consider experience, skills, education, certifications, and geographic location among other factors. This job is also eligible for our Kemper benefits package (Medical, Dental, Vision, PTO, 401k, etc.)

Kemper is proud to be an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran, disability status or any other status protected by the laws or regulations in the locations where we operate. We are committed to supporting diversity and equality across our organization and we work diligently to maintain a workplace free from discrimination. Kemper is focused on expanding our Diversity, Equity and Inclusion efforts to align with our vision, mission, and guiding principles.

Kemper does not accept unsolicited resumes through or from search firms or staffing agencies. All unsolicited resumes will be considered the property of Kemper and Kemper will not be obligated to pay a placement fee.

Kemper will never request personal information, such as your social security number or banking information, via text or email.  Additionally, Kemper does not use external messaging applications like WireApp or Skype to communicate with candidates.  If you receive such a message, delete it.