Machine Learning Engineer

Kemper•Jacksonville, AL

19h•Remote

About The Position

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: The data science and analytics ecosystem is a driver of significant competitive advantage for Kemper and is critical to the organization’s success. The Kemper Analytics Foundation Services team has an immediate opening for an individual to make a lasting impact through building, deploying, and supporting; Machine Learning/Artifical Intelligence (ML/AI) tools and internal data science work products . At this level expected that an ML Ops engineer will work independently and/or lead/smaller efforts.

Requirements

Proficient in Python programming languages
Proficient with SQL
Proficient with Linux/Unix, bash scripts.
Proficient with API development
Proficient with AWS tools such as S3, Kubernetes, EC2, and containerization.
Proficient with data formats such as JSON and XML
Proficient with GitLab
Familiar with SDLC
Experience with Jenkins, Control-M a plus
Experience in financial services a plus
Proficiency with at least one compiled language preferred
Graduate degree in a quantitative field: Mathematics, Statistics, CS, Physics or 5+ years of experience in DevOps, MLOps, or Software engineering
Self-directed
Sponsorship is not accepted for this opportunity
This is a remote opporutnity that can be worked from a US-based home with up to 10% domestic travel required.
The applicant will be required to work Central or Eastern hours.

Responsibilities

Work unsupervised either individually or as part of a team to build, deploy, and support real-time and batch analytics/data science applications
Work unsupervised either individually or as part of a team to build, deploy, and support ML/AI tools for internal users
Contribute to the improvement of internal analytics capabilities, processes and infrastructure.
Collaborate with the business, IT, Model Risk Management, and Enterprise Data Office to responsibly and efficiently support analytics and data science.