As a seasoned Data Science Delivery Leader, you will be responsible for leading the end-to-end delivery of large, complex Data Science, Advanced Analytics, AI, GenAI, and Agentic AI programs across multiple business verticals. Working within the Data Science Practice, you will 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 solid 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.- Identify, assess, and mitigate delivery risks and dependencies proactively, including model performance, scalability, ethical AI, and regulatory risks.- Lead and manage delivery teams of data scientists, ML engineers, GenAI engineers, data engineers, and analysts to ensure execution excellence.- Set clear delivery goals, roles, and accountability for large, distributed program teams.- Drive performance management, resource planning, and delivery productivity across traditional AI and GenAI/Agentic AI workloads.- Partner closely with business and vertical leaders to translate business requirements into scalable AI, GenAI,



and agent-based delivery plans.- Communicate program progress, risks, and outcomes clearly to senior leadership and client stakeholders, including AI-specific metrics and value realization.- Ensure high levels of stakeholder satisfaction through predictable, transparent, and outcome-driven delivery.- Ensure consistent application of AI/ML and GenAI delivery best practices, tools, and quality benchmarks.- Drive continuous improvement in delivery processes to enhance efficiency, reliability, and reusability of AI and GenAI solutions.- Support presales and transition activities through delivery planning, solution estimates, execution readiness, and risk assessments.**Required Qualifications**- 17 years of overall experience, with 810 years in Data Science / Advanced Analytics / AI delivery roles.- Strong hands-on technical foundation in Machine Learning, AI, Generative AI, and Agentic AI concepts, with the ability to guide teams in depth.- 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 (Tensor Flow, PyTorch, scikit-learn) and exposure to LLM ecosystems.- Excellent communication, stakeholder management, and problem-solving skills.**Preferred Skills**- Experience delivering AI, GenAI,



and agent-based solutions on cloud platforms (AWS, Azure, GCP).- Exposure to LLM platforms, vector databases, orchestration frameworks, and AI pipelines.- Exposure to big data ecosystems (Spark, Hadoop, Hive). As a seasoned Data Science Delivery Leader, you will be responsible for leading the end-to-end delivery of large, complex Data Science, Advanced Analytics, AI, GenAI, and Agentic AI programs across multiple business verticals. Working within the Data Science Practice, you will 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.- Identify, assess, and mitigate delivery risks and dependencies proactively, including model performance, scalability, ethical AI, and regulatory risks.- Lead and manage delivery teams of data scientists, ML engineers, GenAI engineers, data engineers, and analysts to ensure execution excellence.- Set clear delivery goals, roles

📌 Delivery Head - Data Science (Yelahanka) (India)
🏢 Tredence
📍 India