Data Scientist & Team Lead

Department: Engineering / Data Science Location: Work from Office (6 Days a Week) Employment Type: Full-Time Experience Level: 23 Years in Data Science & AI/ML Salary/Compensation: Competitive / Based on experience About the Role We are seeking a highly skilled and proactive Data Scientist & Team Lead to spearhead our data science initiatives and guide our technical execution. In this role, you will bridge the gap between high-level business strategy and handson AI/ML development. You will be responsible for architecture decisions, deployment pipelines, and managing a small, agile team of developers and interns to deliver scalable, intelligent enterprise systems. Key Responsibilities Technical Leadership: Mentoring and guiding junior developers and interns, conducting code reviews, and establishing engineering best practices for the data science workflow. End-to-End ML Architecture: Designing, building, and deploying scalable machine learning, deep learning, and predictive models into robust production environments. Strategic Feature Delivery: Collaborating with product managers and backend teams to turn complex corporate data and business objectives into smart application features. Model Lifecycle Management (MLOps): Overseeing data pipelines, monitoring production model drift, and optimizing clouddeployed algorithms for low latency and high accuracy. Innovation & R&D: Researching and implementing stateoftheart AI workflows, custom LLM finetuning pipelines, and prompt engineering frameworks to keep our platform ahead of the curve. Required Skills & Qualifications Experience: 23 years of proven industry experience working as a Data Scientist or AI/ML Engineer, with a track record of shipping models to production. Education: B.Tech, M.Tech, MCA, BCA, or a related technical degree paired with an advanced portfolio of realworld AI applications. Deep Technical Expertise: Mastery of Python and standard data frameworks (NumPy, Pandas, ScikitLearn, PyTorch, or TensorFlow). Advanced AI Foundations: Deep understanding of neural networks, natural language processing (NLP), computer vision, and generative AI patterns (LLM architectures, vector databases, RetrievalAugmented Generation/RAG). Database & Cloud Proficiency: Strong mastery of SQL/NoSQL databases and deployment tools (Docker, AWS, GCP, or Azure). Leadership Traits: Excellent communication and project management skills, with a natural capability to lead sprints, unblock technical hurdles, and drive team ownership. .