Data Scientist

As a Data Scientist specializing in GenAI and Machine Learning with 3+ years of experience, your role will involve working on end-to-end data projects. You will be responsible for analyzing large datasets to derive business insights, designing and optimizing ML and GenAI models, and developing RAG pipelines to enhance model accuracy and contextual awareness. Additionally, you will build data pipelines, collaborate with engineering teams for model deployment, and stay updated on the latest advancements in GenAI and applied ML research. Key Responsibilities: - Analyze large datasets to generate actionable business insights. - Design, train, and optimize ML and GenAI models for text generation, summarization, classification, and recommendation. - Develop and maintain RAG pipelines to enhance model accuracy and contextual awareness. - Implement and fine-tune LLMs using frameworks like LangChain, LlamaIndex, or Hugging Face Transformers. - Build data pipelines and automation workflows for scalable model deployment. - Collaborate with engineering teams to operationalize AI models using cloud services such as AWS SageMaker, Azure ML, GCP Vertex AI. - Conduct exploratory data analysis (EDA), feature engineering, and model evaluation using statistical and ML methods. - Visualize data and insights using tools like Tableau, Power BI, or Plotly Dash. - Document experiments, performance metrics, and ensure reproducibility of models. - Stay updated on the latest developments in GenAI, LLMs, and applied ML research. Qualifications Required: - Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, or a related field. - 3+ years of experience as a Data Scientist, ML Engineer, or AI Researcher. - Strong proficiency in Python (pandas, numpy, scikit-learn, matplotlib, seaborn). - Solid understanding of machine learning algorithms, model evaluation, and data preprocessing. - Experience building or fine-tuning LLMs and implementing RAG pipelines. - Familiarity with GenAI frameworks such as LangChain, LlamaIndex, OpenAI API, Hugging Face. - Experience with SQL and working with large, real-world datasets. - Exposure to cloud platforms (AWS, Azure, or GCP) and containerization (Docker, Kubernetes). - Experience with version control (Git) and collaborative workflows.,