Full-Time Senior Data Scientist

Senior Data Scientist

The ideal Senior Data Scientist candidate will have insurance industry experience with Natural Language Processing (NLP) and possibly Computer Vision (CV), especially for data extraction. They must be skilled in transfer learning and have an understanding of, and capability in, Deep Learning (DL).

They should be able to perform work in these areas using a cloud environment like Databricks on Azure with Python in a notebook and IDE environment. They should also have version control experience with Git.

Experience navigating API-based generative AI models, such as those from OpenAI, is required for developing solutions.

The role requires collaborative, transparent work, and a commitment to improving the overall team's skillset.

Responsibilities:

• Deliver production-quality solutions for data extraction, classification, triaging, routing, search, etc.
• Programmatically explore data, derive statistically sound insights, and communicate findings to colleagues.
• Label and validate datasets of various sizes using manual, programmatic, and AI-driven approaches.
• Evaluate the performance of models and solutions using statistical benchmarks.
• Collaborate with scientists, engineers, product owners, and business customers to develop solutions that meet business needs.
• Create, contribute to, and improve technical and non-technical documentation of solutions.

Required Skills:

• Experience applying quantitative methods in a corporate environment
• Python proficiency with a focus on functional programming, including dependency management, virtual environments, and version control with Git
• Expertise with cloud computing platforms like Azure
• Strong understanding of supervised and unsupervised learning, and experience with deep learning and transfer learning
• Experience with generative algorithms (e.g., GAN, VAE) and foundation models (e.g., GPT-4o, SAM, Mistral)
• Experience in developing solutions from inception through deployment

Desired Skills:

• Graduate degree in a quantitative field
• Experience with sequential algorithms (e.g., LSTM, RNN, GRU)
• Experience evaluating the ethical implications of AI and strategies for control
• Bachelor's degree in Computer Science, Information Technology, Data Analytics, or equivalent

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