Manager Data Science

Location(s)

Details

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. 

Data Science is a driver of significant competitive advantage for Kemper and is critical to the organization’s success. As a member of the Kemper Auto Data Science team, this position is responsible for managing a small team of data scientists and data engineers to deliver analytical solutions on small scale projects.

Responsibilities:

• Manages a small team of data scientists and data engineers to research, design, build, and refine analytical solutions.
• Presents insights, results, and recommendations to external business partners and senior leadership teams.
• Manages project scope, expectations, and timelines.
• Communicates project progress and challenges to business partners and senior leadership team.
• Follows the model governance process including planning, documentation, and review.
• Assists in training sessions on statistical modeling and AI/ML techniques.

Qualifications:

• Graduate degree in Mathematics, Statistics, Engineering, or other STEM field with 6-8 years of experience in insurance industry or related industry in a data science/analytics environment.
• PhD in Mathematics, Statistics, Engineering, or other STEM fields preferred with 4-6 years of experience in insurance industry or related industry in a data science/predictive environment.
• Prior experience mentoring or managing talent.
• At least 6 years of firsthand experience with statistical modeling and AI/ML platforms.
• Proficient in Python programming language (scikit-learn, pandas, numpy, scipy, matplotlib, etc.).
• Proficiency and experience with several modeling techniques such as generalized linear models, decision trees, ensemble learning, regularized models (ridge/lasso/nets), clustering, and neural networks.
• Some experience with natural language processing is preferred.
• Prior experience working with imbalanced datasets and AWS is a plus.
• Ability to work with various data formats. This includes relational databases (especially), delimited text files, data frames, and JSONs.
• Excellent overall communication skills, particularly possessing the ability to translate technical results for wide audiences.

The range for this position is $112100 to $186900. When determining candidate offers, we consider experience, skills, education, certifications, and geographic location among other factors.  This job is eligible for an annual discretionary bonus and Kemper benefits (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 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.  

#LI-WH-1