Staff AIML Data Scientist

Job Description Press Ganey is seeking a Staff Data Scientist with expertise in large language models (LLMs), Generative AI (GenAI), and agentic frameworks to join our forward-thinking team. This role focuses on developing advanced AI models and deploying them in chat-based interfaces, creating intelligent, autonomous systems for seamless and impactful user experiences. The ideal candidate will lead data science initiatives, collaborate closely with interdisciplinary teams, and advance our capabilities in AI-driven interaction, personalization, and automation. Duties & Responsibilities Lead the research, development, and optimization of LLMs and GenAI models, enhancing scalability, efficiency, and response accuracy. Collaborate with machine learning engineers, product managers, and other team members to design and implement AI-powered chat interfaces and autonomous agent frameworks. Develop experimental strategies to test new models and frameworks, perform rigorous evaluation, and improve user interaction and adaptability in chat applications. Conduct end-to-end model lifecycle management, from data processing and model training to deployment and maintenance. Ensure adherence to best practices in data security, privacy, and ethical AI, aligning model development with organizational values and compliance standards. Proactively monitor model performance, analyze results, and integrate feedback loops to support continuous learning and model refinement. Maintain comprehensive documentation on model methodologies, code implementations, data workflows, and deployment processes, promoting reproducibility and collaborative transparency. Mentor junior data scientists, provide technical guidance, and establish best practices to elevate data science quality across the team. Technical Skills Expertise in LLMs, Transformer-based architectures, and Generative AI models. Strong knowledge of NLP methods and frameworks, especially in conversational AI. Familiarity with agent-based architectures supporting autonomous decision-making and interactive user experiences. Proficiency in statistical modeling, hypothesis testing, and data analysis techniques to drive model insights and improvements. Strong Python skills, with experience in data science and ML libraries such as PyTorch, TensorFlow, or scikit-learn. Understanding of data processing and ETL workflows; experience with distributed data processing frameworks like Apache Spark is a plus. Familiarity with cloud-based ML solutions (AWS, GCP, or Azure) for training, deployment, and monitoring. Knowledge of MLOps principles, with experience in model versioning, CI/CD, and workflow management tools (e.g., MLflow, Kubeflow, Airflow). Exposure to containerization and microservices. Familiarity with Databricks is a plus. Qualifications: 5+ years of experience in machine learning, with a focus on NLP, generative AI, or agentic systems. Bachelor's degree in Computer Science, Engineering, Data Science, or a related field. Proven experience deploying AI models in production environments, especially within chat or agent frameworks. Demonstrated ability to communicate complex technical concepts clearly to both technical and non-technical audiences. Strong problem-solving, analytical, and collaborative skills, with the ability to work independently and within a team.

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