Data Scientist Job Description

BKC, Mumbai (WFO)

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.