Forsta
Staff AI/ML Data Scientist
Forsta, Chicago, Illinois, United States, 60290
PG Forsta is the leading experience measurement, data analytics, and insights provider for complex industries—a status we earned over decades of deep partnership with clients to help them understand and meet the needs of their key stakeholders. Our earliest roots are in U.S. healthcare –perhaps the most complex of all industries. Today we serve clients around the globe in every industry to help them improve the Human Experiences at the heart of their business. We serve our clients through an unparalleled offering that combines technology, data, and expertise to enable them to pinpoint and prioritize opportunities, accelerate improvement efforts and build lifetime loyalty among their customers and employees.
Like all great companies, our success is a function of our people and our culture. Our employees have world-class talent, a collaborative work ethic, and a passion for the work that have earned us trusted advisor status among the world’s most recognized brands. As a member of the team, you will help us create value for our clients, you will make us better through your contribution to the work and your voice in the process. Ours is a path of learning and continuous improvement; team efforts chart the course for corporate success.
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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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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