Senior Data Scientist – Generative AI

Become a part of our caring community   We are looking for a Senior Data Scientist to design and deliver Generative AI applications as part of the Growth Analytics & AI team. You will focus on building innovative, scalable, and reliable LLM‑based solutions that produce insights from conversational and long‑form unstructured data to inform business strategy, increase operational efficiency, and improve customer experience. The ideal candidate combines strong applied GenAI and machine learning expertise with solid software engineering practices, demonstrates curiosity in exploring new approaches and use cases, and communicates effectively with both technical and non‑technical stakeholders. This role partners with product, engineering, and platform teams to translate complex business problems into production‑ready AI solutions and move high‑value use cases from concept to impact..

Design, build, and deploy LLM-based applications for conversational intelligence and insight generation. Develop multi-step AI workflows, including retrieval, orchestration, routing, and tool-using patterns. Define and implement evaluation approaches for LLM applications, including response quality, reliability, safety, and value. Work with large-scale structured and unstructured data using modern data platforms (e.g., Spark, Databricks, Snowflake). Partner with engineering teams to move GenAI solutions from prototype to production. Write clean, maintainable code and contribute to shared development practices such as version control, documentation, and code review. Ensure solutions align with enterprise standards for security, privacy, compliance, and responsible AI. Use your skills to make an impact   Required Qualifications Bachelor's degree and 5+ years of experience, Master's degree and 3+ years, or PhD candidate in computer science, data science, engineering, or a related quantitative field. Strong proficiency in Python and modern development practices for AI applications. Expertise in working with natural language data and building text-based products, using both classic and state-of-the-art NLP techniques (e.g. text mining, word embeddings, transformer-based models) Experience with LLM prompt engineering and architectural patterns for LLM systems (e.g., retrieval‑augmented generation, multi‑agent designs). Hands‑on experience building tool‑integrated and agent‑based LLM workflows using frameworks such as LangChain, LangGraph, AutoGen, CrewAI, or similar. Experience working with cloud and data platforms such as Azure, Databricks, GCP, and Snowflake. Experience designing, evaluating, and supporting AI applications in production or enterprise environments. Experience with data governance, privacy, security, and compliance requirements. Strong communication skills and ability to work with technical and non-technical teams.

Ph.D. in Computer Science or a related quantitative field. Experience in the healthcare, medical, or pharmaceutical industry. Hands-on experience in MLOps, DevOps, or software engineering. Demonstrated depth in machine learning and generative AI, with a strong applied understanding of LLM behavior, evaluation, reliability, and trade‑offs. Proven hands‑on experience building end‑to‑end GenAI and agentic AI solutions. Experience building GenAI solutions that operate on long‑context data such as chats, transcripts, and long‑form documents in real‑world, production scenarios.

The candidate must be able to work within the Eastern or Central Standard Time zones. Work at Home Requirements: To ensure Home or Hybrid Home/Office employees’ ability to work effectively, the self-provided internet service of Home or Hybrid Home/Office employees must meet the following criteria: At minimum, a download speed of 25 Mbps and an upload speed of 10 Mbps is required; wireless, wired cable or DSL connection is suggested. In certain