Delivery Head - Data Science

As a seasoned Data Science Delivery Leader, your role will involve leading the end-to-end delivery of large, complex Data Science, Advanced Analytics, AI, GenAI, and Agentic AI-driven programs across multiple business verticals. You will be part of the Data Science Practice and collaborate horizontally with vertical and functional teams to ensure consistent, high-quality delivery outcomes. Key Responsibilities: - Own and drive end-to-end delivery of large-scale, multi-year Data Science, AI, GenAI, and Agentic AI programs, ensuring adherence to scope, timelines, quality, and cost. - Provide strong technical oversight across solution design, ML/AI model development, GenAI solution architecture, agent workflows, validation, deployment, and productionization. - Act as the senior escalation point for critical technical, architectural, and delivery issues, including GenAI and AI-agent related risks. - Lead multiple concurrent programs and projects using Agile, hybrid, or waterfall delivery models, including complex AI and GenAI engagements. - Establish and run delivery governance, cadence reviews, and executive-level status reporting for AI and GenAI initiatives. - Lead and manage delivery teams of data scientists, ML engineers, GenAI engineers, data engineers, and analysts to ensure execution excellence. - Partner closely with business and vertical leaders to translate business requirements into scalable AI, GenAI, and agent-based delivery plans. - Ensure consistent application of AI/ML and GenAI delivery best practices, tools, and quality benchmarks. Qualifications Required: - 17+ years of overall experience, with 8-10+ years in Data Science/Advanced Analytics/AI delivery roles. - Strong hands-on technical foundation in Machine Learning, AI, Generative AI, and Agentic AI concepts. - Proven experience managing large programs, multi-project portfolios, and complex AI/GenAI delivery engagements. - Solid expertise in program and project management methodologies and delivery governance models. - Experience with tools and technologies such as Python, R, ML frameworks (TensorFlow, PyTorch, scikit-learn) and exposure to LLM ecosystems. - Excellent communication, stakeholder management, and problem-solving skills. The above details are extracted from the provided job description. As a seasoned Data Science Delivery Leader, your role will involve leading the end-to-end delivery of large, complex Data Science, Advanced Analytics, AI, GenAI, and Agentic AI-driven programs across multiple business verticals. You will be part of the Data Science Practice and collaborate horizontally with vertical and functional teams to ensure consistent, high-quality delivery outcomes. Key Responsibilities: - Own and drive end-to-end delivery of large-scale, multi-year Data Science, AI, GenAI, and Agentic AI programs, ensuring adherence to scope, timelines, quality, and cost. - Provide strong technical oversight across solution design, ML/AI model development, GenAI solution architecture, agent workflows, validation, deployment, and productionization. - Act as the senior escalation point for critical technical, architectural, and delivery issues, including GenAI and AI-agent related risks. - Lead multiple concurrent programs and projects using Agile, hybrid, or waterfall delivery models, including complex AI and GenAI engagements. - Establish and run delivery governance, cadence reviews, and executive-level status reporting for AI and GenAI initiatives. - Lead and manage delivery teams of data scientists, ML engineers, GenAI engineers, data engineers, and analysts to ensure execution excellence. - Partner closely with business and vertical leaders to translate business requirements into scalable AI, GenAI, and agent-based delivery plans. - Ensure consistent application of AI/ML and GenAI delivery best practices, tools, and quality benchmarks. Qualifications Required: - 17+ years of overall experience, with 8-10+ years in Data Science/Advanced Analytics/AI delivery roles. - Strong hands-on technical foundation in Machine Learning, AI, Generative AI, and Agentic AI concepts. - Proven experience managing large programs, multi-project portfolios, and complex AI/GenAI delivery engagements. - Solid expertise in program and project management methodologies and delivery governance models. - Experience with tools and technologies such as Python, R, ML frameworks (TensorFlow, PyTorch, scikit-learn) and exposure to LLM ecosystems. - Excellent communication, stakeholder management, and problem-solving skills. The above details are extracted from the provided job description.