Data Scientist II, TDI

As a Data Scientist II at NPS Prism, a market-leading SaaS business owned by Bain & Company, you will play a crucial role in developing and deploying AI solutions across various use cases, including classical machine learning and modern AI systems. Your responsibilities will include designing, validating, and optimizing predictive models, deploying LLM-based and Generative AI solutions, building multi-agent systems, applying statistical analysis for business decisions, and collaborating with cross-functional teams. You will also ensure production readiness, analyze datasets for actionable insights, communicate findings to stakeholders, contribute to code reviews, and manage projects independently in dynamic environments. Key Responsibilities: - Develop and deploy AI solutions across ML and other genAI use cases. - Design, build, validate and optimize predictive models, including regression, tree-based models, ensemble methods, and deep learning architectures. - Develop and deploy LLM-based and Generative AI solutions, such as RAG and prompt engineering. - Build multi-agent systems and tool-integrated AI solutions for analytics automation and conversational interfaces. - Apply statistical analysis and experimental design to inform business decisions. - Collaborate with cross-functional teams. - Ensure production readiness through monitoring, model governance, and performance tracking. - Analyze structured and unstructured datasets to generate actionable insights. - Communicate analytical findings clearly to stakeholders. - Contribute to code reviews and continuous improvement of AI infrastructures. - Independently manage projects in evolving environments. Qualifications Required: - Education: Bachelors or Masters degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or related fields. - Experience: 3+ years in data science or applied machine learning roles. - Demonstrated experience in delivering regression and/or classification models in production. - Hands-on experience in building and deploying LLM-based or Generative AI applications. - Proficiency in Python. - Solid foundation in classical ML techniques, statistics, regression, and classification. - Experience with LLMs, Generative AI, and agentic frameworks. - Familiarity with vector databases and embedding pipelines. - Experience deploying ML/LLM solutions in production with MLOps practices on cloud platforms. - Strong problem-solving and communication skills. As a Data Scientist II at NPS Prism, a market-leading SaaS business owned by Bain & Company, you will play a crucial role in developing and deploying AI solutions across various use cases, including classical machine learning and modern AI systems. Your responsibilities will include designing, validating, and optimizing predictive models, deploying LLM-based and Generative AI solutions, building multi-agent systems, applying statistical analysis for business decisions, and collaborating with cross-functional teams. You will also ensure production readiness, analyze datasets for actionable insights, communicate findings to stakeholders, contribute to code reviews, and manage projects independently in dynamic environments. Key Responsibilities: - Develop and deploy AI solutions across ML and other genAI use cases. - Design, build, validate and optimize predictive models, including regression, tree-based models, ensemble methods, and deep learning architectures. - Develop and deploy LLM-based and Generative AI solutions, such as RAG and prompt engineering. - Build multi-agent systems and tool-integrated AI solutions for analytics automation and conversational interfaces. - Apply statistical analysis and experimental design to inform business decisions. - Collaborate with cross-functional teams. - Ensure production readiness through monitoring, model governance, and performance tracking. - Analyze structured and unstructured datasets to generate actionable insights. - Communicate analytical findings clearly to stakeholders. - Contribute to code reviews and continuous improvement of AI infrastructures. - Independently manage projects in evolving environments. Qualifications Required: - Education: Bachelors or Masters degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or related fields. - Experience: 3+ years in data science or applied machine learning roles. - Demonstrated experience in delivering regression and/or classification models in production. - Hands-on experience in building and deploying LLM-based or Generative AI applications. - Proficiency in Python. - Solid foundation in classical ML techniques, statistics, regression, and classification. - Experience with LLMs, Generative AI, and agentic frameworks. - Familiarity with vector databases and embedding pipelines. - Experience deploying ML/LLM solutions in production with MLOps practices on cloud platforms. - Strong problem-solving and communication skills.