Data Scientist

Qualification

Master's or Ph.D. in computer science, statistics, math, data science, or a related field, or at least two years of work in a similar role. Technical Knowledge – Programming : Skill with Python and related tools (such as NumPy, Pandas, scikit-learn, TensorFlow, and PyTorch). Statistics & Math: Strong knowledge of advanced math concepts (such as linear algebra, calculus, and optimization) and statistical ideas (such as probability, hypothesis testing, and regression). Machine Learning: Supervised, uncontrolled, reinforcement learning, and deep learning are some of the machine learning and artificial intelligence (AI) models that have been built and used successfully in the past. Prompt & Feature Engineering: Proven track record of creating useful prompts for LLM-based solutions, along with strong feature engineering skills to improve model performance. LLM & Generative AI Tools: Know how to use LangChain, LangGraph, OpenAI, Claude, Gemini, LLAMA, and other similar tools for big language model projects. Infrastructure and Data Handling: Knowledge of data engineering techniques, such as ETL processes, big data solutions, and cloud-based platforms (AWS, Azure, or GCP). It would be help