Manager - Data Science

<p><span style="font-family:Georgia;"><span style="font-family:DarwinSans;">Designation: </span>Manager - Data Science</span><br /><span style="font-family:Georgia;"><span style="font-family:DarwinSans;">Experience:</span> 10 to 15 Years</span><br /><span style="font-family:Georgia;"><span style="font-family:DarwinSans;">Location:</span> Chennai</span><br /><br /><span style="font-family:Georgia;"><span style="font-family:DarwinSans;">Job Description:</span></span><br /><br /><span style="font-family:Georgia;">We are seeking an L4 Data Scientist / AI Architect Manager to lead our AI initiatives and drive the adoption of cutting-edge Machine Learning and Generative AI technologies. In this dual-hat role, you will define the technical architecture of our enterprise AI systems while directly managing and mentoring a high-performing team of data scientists and ML engineers. You will act as the crucial bridge between business strategy and technical execution, ensuring our AI solutions are innovative, scalable, and deliver measurable business value.</span><br /><br /><span style="font-family:Georgia;"><span style="font-family:DarwinSans;">Responsibilities:</span></span><br /><br /></p><div><span style="font-family:Georgia;">Architect AI Solutions: Design and build scalable, production-ready AI/ML systems and Generative AI pipelines (e.g., RAG, fine-tuned LLMs).</span><br /><br /></div><div><span style="font-family:Georgia;">Team Leadership: Manage, mentor, and grow a technical team of data scientists and engineers, fostering a culture of excellence and continuous learning.</span><br /><br /></div><div><span style="font-family:Georgia;">Strategic Direction: Partner with Product and Engineering leadership to define the AI roadmap and translate business objectives into actionable technical deliverables.</span><br /><br /></div><div><span style="font-family:Georgia;">Technical Oversight: Lead system design reviews, conduct code reviews, and establish best practices for MLOps, model deployment, and AI governance.</span><br /><br /></div><div><span style="font-family:Georgia;">Hands-on Development: Actively contribute to complex coding tasks, rapid prototyping, and solving the hardest architectural bottlenecks.</span><br /><br /></div><div><span style="font-family:Georgia;">Cross-Functional Delivery: Collaborate seamlessly with data engineering, software development, and business stakeholders to integrate AI models into user-facing applications.</span></div><p><br /><span style="font-family:Georgia;"><span style="font-family:DarwinSans;">Skills:</span></span><br /></p><p><br /><span style="font-family:Georgia;">AI/ML Architecture: End-to-end system design for scalable AI solutions. Programming: Python (Expert). GenAI & LLMs: RAG pipelines, fine-tuning, LangChain/LlamaIndex, Prompt Engineering. Deep Learning: PyTorch or TensorFlow. MLOps: Model deployment, serving, and monitoring (MLflow, Kubeflow, Docker, Kubernetes). Leadership: Technical team management, code reviews, and cross-functional stakeholder communication.</span><br /><br /><span style="font-family:Georgia;">Data Processing: SQL, Apache Spark, Databricks, or Snowflake. Vector Databases: Pinecone, Milvus, Weaviate, or Qdrant. Cloud Infrastructure: AWS (SageMaker), GCP (Vertex AI), or Azure ML (plus general cloud networking/security). AI Governance: Data privacy, bias mitigation, and responsible AI frameworks. Additional Languages: C++, Go, or Java. Product Delivery: Agile/Scrum methodologies and translating business KPIs into technical metrics.</span></p><p><br style="color:rgb(19,19,19);" /></p>