Algorithmic Model Development: Design, build, and maintain production-grade machine learning and statistical models to automate risk assessment and underwriting decisions.
Systems Architecture and Engineering: Architect and build robust, scalable, and secure data pipelines and infrastructure to support model training, deployment, and monitoring.
Collaboration and Integration: Collaborate closely with Data Scientists, Software Engineers, and Underwriters to integrate models into our core platform and ensure high availability and performance.
Technical Leadership: Provide mentorship and guidance to other engineers on our team, establishing best practices for software engineering, model development, and code quality.
Research and Innovation: Stay up-to-date with the latest advancements in AI, machine learning, and statistical modelling, and evaluate their potential application to Ki's business.

Requirements

Master’s or PhD in Computer Science, Machine Learning, Statistics, Mathematics, or a highly quantitative field, or equivalent commercial experience.
Background in designing, building, and deploying complex machine learning models in production environments.
Strong software engineering skills with deep proficiency in Python and libraries like NumPy, Pandas, Scikit-learn, PyTorch, and TensorFlow.
Working knowledge of cloud platforms (specifically AWS) and containerization technologies (such as Docker and Kubernetes).
Excellent communication skills, enabling you to explain complex technical concepts clearly to cross-functional stakeholders.
Ability to mentor engineers and establish team-wide best practices for software engineering, model development, and code quality.
Commercial acumen, with an understanding of the insurance or financial services industry (highly desirable).

Staff Algorithm Engineer