Senior Data Informatics Manager AI/ML Engineering Development

Senior Data Informatics Manager AI/ML Engineering Development

• Lead the vision, roadmap, and execution of enterprise AI/ML and data informatics initiatives that improve operational efficiency, decision support, and service quality.
• Drive the design, development, and deployment of advanced analytical solutions using classification, clustering, regression, time series analysis, neural networks, and statistical modeling .
• Oversee the development of Generative AI and NLP-based solutions , including applications involving summarization, text mining, sentiment analysis, automation, and LLM-enabled workflows.
• Lead the creation of context-aware conversational systems , including RAG-enabled assistants, chatbot platforms, and knowledge-driven AI applications .
• Guide the implementation of multi-agent and agentic AI systems to automate complex workflows, improve orchestration, and enhance enterprise decision-making.
• Partner closely with cross-functional stakeholders across engineering, operations, product, cybersecurity, and business teams to identify high-value opportunities and translate them into scalable AI/ML solutions.
• Establish and promote best practices across the AI/ML lifecycle, including data preparation, model development, validation, deployment readiness, performance monitoring, and continuous improvement.
• Mentor and develop high-performing teams of data scientists, ML engineers, and informatics professionals, fostering technical excellence, innovation, and business impact.
• Communicate technical strategy, solution value, and execution progress effectively to senior leaders and diverse stakeholder groups.

• Master's degree or higher in Data Science, Computer Science, Statistics, Applied Mathematics, Engineering, or a related quantitative discipline with research focus in data mining, machine learning, text mining, databases, statistics, and forecasting .
• 5+ years of progressive experience in data science, analytics, machine learning, or informatics, including experience delivering enterprise-scale solutions.
• Demonstrated expertise in machine learning and statistical methods , including classification, clustering, regression, time series analysis, hypothesis testing, Bayesian analysis, and neural networks.
• Strong experience with Generative AI technologies , including LLMs, OpenAI tools, NLP techniques, LangChain, LangGraph, AutoGen, swarm or multi-agent frameworks, and vector database-based architectures .
• Proven experience building or leading solutions involving RAG, advanced chatbots, knowledge-aware AI systems, and intelligent workflow automation .
• Expertise in text analytics, summarization, sentiment analysis, and unstructured data processing for real-world business applications.
• Proficiency with modern analytics and ML development tools such as Python, R, SAS, TensorFlow, PyTorch, SQL , and data visualization platforms.
• Strong communication and leadership capabilities, with the ability to influence technical and business stakeholders and convert complex challenges into scalable solutions.

• Experience leading teams or mentoring technical professionals in data science, AI/ML engineering, or data informatics environments .
• Hands-on experience with LLM-powered automation, systems intelligence workflows, or agentic AI .
• Demonstrated ability to quickly adopt emerging technologies and apply them effectively to create innovative, production-relevant solutions.

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