Senior Data Scientist – Generative AI

Accountabilities:

• Design, develop, and deploy production-ready LLM applications focused on conversational intelligence, insight generation, and long-form unstructured data.
• Build multi-step AI workflows incorporating retrieval, orchestration, routing, tool use, and agentic patterns.
• Develop robust evaluation frameworks for LLM applications, measuring response quality, reliability, safety, performance, and business value.
• Apply natural language processing and machine learning techniques to extract meaningful insights from conversations, transcripts, documents, and other text-based data.
• Work with large-scale structured and unstructured datasets using modern platforms such as Spark, Databricks, and Snowflake.
• Partner closely with product, engineering, and platform teams to transition GenAI prototypes into scalable, reliable production solutions.
• Develop clean, maintainable Python code and contribute to engineering best practices including version control, documentation, testing, and code reviews.
• Design end-to-end GenAI and agentic AI solutions while balancing model capabilities, latency, reliability, cost, and business requirements.
• Ensure AI solutions meet enterprise standards for data governance, privacy, security, compliance, and responsible AI.
• Collaborate with technical and non-technical stakeholders to translate complex business challenges into practical AI solutions and communicate results effectively.
• Explore emerging GenAI approaches, frameworks, and technologies to identify new opportunities for automation, insight generation, and customer impact.

Requirements:

• Bachelor’s degree with 5+ years of relevant experience, Master’s degree with 3+ years of experience, or PhD-level study in computer science, data science, engineering, or another quantitative discipline.
• Strong proficiency in Python and modern software development practices for AI and machine learning applications.
• Deep experience working with natural language data and building text-based products using techniques such as text mining, embeddings, transformers, and modern NLP approaches.
• Hands-on expertise with LLM prompt engineering and architectural patterns such as retrieval-augmented generation (RAG) and multi-agent systems.
• Experience developing tool-integrated and agent-based LLM workflows using frameworks such as LangChain, LangGraph, AutoGen, CrewAI, or comparable technologies.
• Experience with cloud and modern data platforms, including Azure, Databricks, Google Cloud Platform, and Snowflake.
• Demonstrated ability to design, evaluate, deploy, and support AI applications in production or enterprise environments.
• Strong understanding of LLM behavior, evaluation methodologies, reliability, safety, and the trade-offs involved in deploying GenAI solutions at scale.
• Experience with data governance, privacy, security, compliance, and responsible AI requirements.
• Strong communication and collaboration skills, with the ability to work effectively across technical, business, product, engineering, and platform teams.
• Experience with MLOps, DevOps, or software engineering practices is preferred.
• A PhD in Computer Science or a related quantitative field is preferred.
• Experience within healthcare, medical, pharmaceutical, or another highly regulated industry is a plus.
• Demonstrated experience building end-to-end GenAI or agentic AI solutions for real-world production use cases is highly valued.
• Experience working with long-context data, including chats, transcripts, and long-form documents, in production environments is preferred.
• Ability to work within the Eastern or Central U.S. time zones.
• For remote work, access to a dedicated workspace and reliable internet service with minimum speeds of approximately 25 Mbps download and 10 Mbps upload is required.
• Ability to travel occasionally for training, meetings, or other business needs.

Benefits:

• Annual base salary range of $117,600–$161,700, depending on location, skills, experience, education, certifications, and other job-related factors.
• Eligibility for a bonus incentive plan based on company and/or individual performance.
• Medical, dental, and vision insurance.
• 401(k) retirement savings plan.
• Paid time off, company holidays, and personal holidays.
• Paid parental and caregiver leave.
• Short-term and long-term disability coverage.
• Life insurance.
• Additional benefits and programs supporting physical, financial, and emotional well-being.
• Remote work flexibility within eligible U.S. locations and time zones.
• Opportunities to work on high-impact Generative AI initiatives involving enterprise-scale data, modern AI architectures, and customer-focused applications.
• A collaborative environment connecting data science, engineering, product, and platform teams.