Kemper is looking for a leader to drive scalable and transparent solutions across the data science lifecycle by leveraging expertise in machine learning, cloud computing, and software engineering best practices.
Requirements
- At least 10 years of firsthand experience with statistical modeling and AI/ML platforms.
- Strong proficiency in Python with a focus on readable, maintainable, and well-documented code.
- Deep knowledge of machine learning and statistical modeling, with experience across supervised, unsupervised, and time series methods.
- 5+ years of hands-on experience with cloud platforms (e.g., AWS, Azure, or Databricks) for data science and machine learning workflows.
- Exposure to reinforcement learning, large language models (LLMs), or other emerging ML techniques
- Understanding of MLOps principles including model packaging, CI/CD workflows, and scalable pipelines (GitLab experience a plus).
Responsibilities
- Leads cross-functional discussions to solve various business problems and design end-to-end AI/ML solutions.
- Presents analytical solutions to external business partners and senior leadership teams.
- Communicates project progress and challenges to external business partners and senior leadership teams.
- Manages project scope, expectations, and timelines.
- Leads model peer reviews with other data science groups and business partners.
- Guides the team in building modular Python code and full-stack frameworks for model development, training, deployment, and scoring.
Other
- Responsible for directing strategic development and solutioning in cross-functional teams.
- Coaches and mentors other team members.
- Maintains cutting-edge technical and industry knowledge.
- Promotes a culture of learning, curiosity, and engineering discipline within the data science team.
- Leads training sessions on statistical modeling, machine learning, and AI techniques.
