Data Scientist

The ideal Mid-Level Data Scientist candidate will have experience applying Natural Language Processing (NLP) and deep learning techniques within the insurance industry, focusing on data extraction challenges. They should be adept in traditional statistical learning and data analysis, capable of independently developing solutions using cloud platforms like Azure and programming in Python with version control through git. This role involves working directly with API-based generative AI models to create impactful solutions. The candidate will collaborate with cross-functional teams, mentor junior team members, and contribute to both technical and non-technical documentation. They should demonstrate strong communication skills, manage their time effectively, and navigate complex and varied technical challenges with ease.

• sDeliver production quality solutions for data extraction, classification, triaging, routing, and searc
• hProgrammatically explore data, derive statistically sound insights, and effectively communicate findings to colleague
• sLead data labeling and validation efforts using manual and AI-driven approache
• sEvaluate model performance, applying both practical and statistical benchmark
• sCollaborate with scientists, engineers, and product owners to develop solution
• sMentor junior team members, guiding them through technical challenge
• sContribute to, improve, and convey technical and non-technical documentatio

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Qualificatio

• nsBachelor's degree in a quantitative field; master's preferred but not requir
• edProven capability in NLP, deep learning, and strong skills in traditional statistical learning and data analys
• isProficiency in Python programming, managing dependencies, and using version control in g
• itExperience in a corporate environment applying quantitative metho
• dsStrong communication skills and ability to manage time effective

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Preferred Qualificati

• onsInsurance experie
• nceExperience with cloud computing platforms, especially Az
• ureUnderstanding of generative algorithms and foundation mod
• elsExperience evaluating ethical implications of

AI