Senior Manager

Role Overview: We are seeking a highly skilled and forward-thinking Manager – Data Science & Generative AI to lead data-driven innovation within our organization. This role requires a blend of technical expertise in machine learning and GenAI, team leadership, and strategic thinking to build scalable solutions and drive business transformation through intelligent systems. As a Manager, you will lead cross-functional teams, guide AI/ML project lifecycles, and help deploy Generative AI models into real-world applications, ranging from content generation to intelligent automation. Key Responsibilities: Lead the end-to-end lifecycle of data science and Generative AI projects—from problem scoping and data exploration to model deployment and performance monitoring. Manage a team of data scientists and ML engineers, providing technical guidance and mentorship. Develop and implement advanced machine learning models including deep learning, NLP, and GenAI architectures (e.g., transformers, LLMs). Collaborate with product, engineering, and business teams to identify AI opportunities, define use cases, and deploy innovative solutions. Evaluate and fine-tune pre-trained foundation models (e.g., GPT, Claude, LLaMA, Gemini) for domain-specific applications using prompt engineering, fine-tuning, or retrieval-augmented generation (RAG). Lead the creation of synthetic data, content generation, and intelligent assistants using GenAI capabilities. Drive responsible AI practices and ensure model transparency, fairness, and compliance with ethical and regulatory guidelines. Contribute to strategic roadmaps for AI adoption across the enterprise. Present findings, models, and strategies to stakeholders and senior leadership. Required Skills & Experience: 6–10 years of experience in Data Science or AI/ML, including at least 2–3 years in a managerial or lead role. Strong proficiency in Python and data science libraries (NumPy, Pandas, scikit-learn, TensorFlow, PyTorch). Proven experience in building and deploying ML models in production environments. Solid experience working with Generative AI tools and platforms (e.g., OpenAI APIs, Hugging Face, LangChain, Vertex AI, Azure OpenAI). Expertise in NLP, LLMs, prompt engineering, fine-tuning, and text generation. Familiarity with cloud platforms (AWS, GCP, Azure) and MLOps pipelines. Strong understanding of data engineering concepts, APIs, and scalable architectures. Excellent problem-solving, project management, and communication skills. Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or related field (PhD is a plus). Nice to Have: Experience with Retrieval-Augmented Generation (RAG) and vector databases (e.g., FAISS, Pinecone, Weaviate). Familiarity with model safety, explainability (XAI), and ethical AI frameworks. Publications or contributions in AI/ML conferences or open-source projects. Hands-on experience in GenAI use cases like document summarization, chatbots, code generation, or marketing automation.