& Summary: We are seeking a highly skilled and visionary Senior Manager – Data Science & AI to lead our advanced analytics and AI/ML initiatives, including next-generation technologies like Generative AI and Agentic AI. The ideal candidate will be responsible for managing data science teams, driving innovation in machine learning model development, and operationalizing AI solutions that deliver measurable business value.

Responsibilities:

· Lead, mentor, and scale a team of data scientists, ML engineers, and AI researchers working on predictive analytics, generative AI models, and agentic AI systems. · Define the AI/ML strategy aligned with business goals and emerging technology trends, including GenAI and agentic AI capabilities. · Oversee the full ML lifecycle: problem formulation, data acquisition, feature engineering, model development, validation, deployment, and monitoring. · Drive the research and development of advanced AI models, including generative models (e.g., GPT, diffusion models), reinforcement learning agents, and autonomous AI systems. · Collaborate with product, engineering, and data engineering teams to integrate AI/ML solutions into scalable production environments. · Implement best practices for MLOps, model governance, explainability, and ethical AI. · Evaluate and adopt state-of-the-art AI technologies, frameworks, and tools (e.g., TensorFlow, PyTorch, Hugging Face, LangChain). · Champion the use of generative AI for use cases such as content generation, code synthesis, conversational agents, and decision automation. · Manage cross-functional projects and collaborate with stakeholders to prioritize AI initiatives based on business impact. · Stay abreast of industry research and contribute to AI community engagement, publications, or conferences as appropriate.

Mandatory skill sets:

· Strong background in Data Science, Machine Learning, Artificial Intelligence, with hands-on experience in developing and deploying models in production. · Deep knowledge of Generative AI technologies — experience working with models such as GPT, BERT, DALL-E, diffusion models, or other generative architectures.

· Understanding of Agentic AI concepts including reinforcement learning, autonomous decision-making systems, and intelligent agents. · Proficiency in ML frameworks and libraries: TensorFlow, PyTorch, Scikit-learn, Hugging Face Transformers, LangChain, etc. · Programming expertise in Python and experience with related ML/AI libraries. · Experience with MLOps practices and tools for CI/CD of machine learning models (e.g., Kubeflow, MLflow, TFX). · Solid grasp of data engineering basics and ability to collaborate effectively with data engineering teams. · Familiarity with cloud platforms (Azure ML, AWS SageMaker, Google Vertex AI, Oracle AI services) for model training and deployment. · Knowledge of AI ethics, fairness, bias mitigation, privacy, and explainability. Leadership & Management: · Proven experience managing data science, ML, or AI teams. · Ability to translate complex AI technologies into business value and actionable insights. · Strong communication and stakeholder management skills. · Experience working in agile delivery environments and managing cross-functional resources. · Demonstrated ability to mentor and develop technical talent.

Preferred skill sets:

· Master’s or PhD degree in Computer Science, Artificial Intelligence, Machine Learning, Statistics, or related field. · Publications or patents in AI fields or participation in AI research communities. · Experience in deploying AI-powered conversational agents, digital assistants, or autonomous AI systems. · Familiarity with natural language processing (NLP), computer vision, or speech AI applications. · Experience with agentic or autonomous AI frameworks and tooling.

Years of experience required:

12 to 16 years

Education qualification:

Graduate Engineer or Management Graduate