Data Scientist Job Description GenAI Data Scientist BKC, Mumbai (WFO) Fulltime to XTGlobal Shift Hours : 8:30 AM - 5:30 PM IST About the Role We are seeking a highly skilled GenAIData Scientist with expertise in Machine Learning (ML), Artificial Intelligence (AI), and Generative AI (GenAI) to join our team. The ideal candidate will have a strong foundation in traditional data science methods along with hands-on experience in building, fine-tuning, and deploying generative AI models for business applications. This role will involve working closely with cross-functional teams to design, develop, and deploy AI/ML solutions, leveraging both classical approaches (predictive modeling, optimization, NLP, forecasting, computer vision) and cutting-edge generative AI techniques (LLMs, diffusion models, multi-modal AI). Key Responsibilities · Develop and deploy end-to-end ML/AI pipelines, from data collection, preprocessing, and feature engineering to model training, evaluation, and deployment. · Apply traditional ML/AI techniques (regression, classification, clustering, recommendation systems, optimization). · Design and implement GenAI solutions using large language models (LLMs), transformers, and multimodal architectures (text, image, audio). · Fine-tune, evaluate, and optimize foundation models (e.g., GPT, LLaMA, Claude, Falcon, Stable Diffusion) for enterprise use cases. · Research, experiment, and prototype cutting-edge AI solutions tailored to business problems. · Collaborate with data engineers, ML engineers, and domain experts to productionize models and integrate them into business workflows. · Containerize and orchestrate models and pipelines (Docker, Kubernetes). · Stay updated with the latest trends in AI, ML, and GenAI, and drive innovation and adoption of new methods. Requirements Required Qualifications: · Bachelor’s degree (B.Tech, BE, or equivalent) in Computer Science, Data Science, AI, or related field. · Advanced degree (M.Tech/MS/MBA/PhD) is a plus but not mandatory. · 3-5 years of experience in ML/AI, with hands-on expertise in building and deploying models. · Functional expertise in at least one business domain (e.g., Supply Chain, Finance, Healthcare, Pharma, Customer Analytics, Manufacturing). · Proficiency in Python, PyTorch/TensorFlow, scikit-learn, Hugging Face, LangChain. · Strong understanding of NLP, predictive modeling, deep learning architectures (CNNs, RNNs, Transformers). · Experience with cloud AI platforms (AWS, Azure, GCP) and MLOps tools (Docker, Kubernetes, CI/CD). · Strong stakeholder management and ability to communicate technical insights in business terms.