Job Description
7+ years of hands-on ML modeling/development experience Background in insurance and underwriting preferred Solid understanding of data analysis and statistical modeling. Knowledge of a variety of machine learning techniques (clustering, decision tree, bagging/boosting artificial neural networks, etc.) and their real-world advantages/drawbacks. Demonstrated track records in experimental design and executions Hands-on experience with data wrangling including fuzzy matching and regular expression. distributed computing and applying parallelism to ML solutions Strong programming skills in Python Solid background in algorithms and a range of ML models Excellent communication skills and ability to work and collaborate cross-functionally with Product, Engineering, and other disciplines at both the leadership and hands-on level Excellent analytical and problem-solving abilities with superb attention to detail Proven experience in providing technical leadership and mentoring to data scientists and strong project management skills with ability to monitor/track performance for enterprise success Experience communicating complex ideas simply, presenting impact, trade-offs, and recommendations to non-technical partners.
testing, logging,...). Working knowledge of core software engineering concepts (version control with Git/GitHub. Working knowledge of NLP, LLMS, RAG architecture, and agent frameworks, including safe automation design and evaluation systems. Experience in insurance, financial services, or related industries is a plus Apply tot his job