Data Scientist

Our company description Mission is a platform for hiring, vetting, and managing software development talent. It enables our clients to connect with the world’s best talent to build mission-critical software products About the Company This enterprise AI company develops decision-making solutions for the global insurance sector. The platform leverages agentic AI to automate and optimize complex workflows, including fraud detection, claims processing, and payment integrity. With a large, specialized data science organization, the firm provides scalable tools to help insurers improve operational efficiency and decision accuracy through advanced machine learning and data processing. What You’ll Do • Build multi-modal data pipelines optimized for large language models and document understanding. • Design and deploy LLM-based solutions including retrieval-augmented generation (RAG), embeddings, and instruction tuning for claims processing. • Develop minimum viable products for agentic AI systems using modern orchestration frameworks and model SDKs. • Create custom interfaces and tools that allow AI agents to query internal databases and integrate with external APIs. • Establish rigorous evaluation frameworks to ensure AI-driven decisions are unbiased, explainable, and compliant with legal standards. • Implement responsible AI practices to mitigate hallucinations and maintain data privacy across all deployed models. • Lead technical workshops with clients to present prototypes, gather feedback, and define product roadmap priorities. What You Bring • 3+ years of experience in data science specifically within the healthcare insurance payment integrity domain. • Expertise in production-level object-oriented programming for building scalable, reliable systems. • Hands-on experience with Large Language Models (LLMs) and generative AI techniques, including RAG and prompt engineering. • Strong foundation in the full machine learning lifecycle, including model evaluation, monitoring, and production deployment. • Proven ability to design data pipelines for document processing, OCR, and multi-modal workflows. • Experience integrating agentic frameworks with cloud-hosted models. • Demonstrated proficiency in client engagement and translating business needs into technical solutions. Nice to Haves • Expertise in the Databricks ecosystem, including data cataloging and delta lake architectures. • Familiarity with distributed data processing and Spark architecture. • Experience using lifecycle management tools for experiment tracking, prompt engineering, and model evaluation.