Data-scientist
• Experience with LangChain, LangGraph, AutoGen, Hugging Face, OpenAI, Gemini, or comparable AI frameworks.
• Experience with ML observability tools such as Weights & Biases, LangSmith, TensorBoard, or similar platforms.
• Knowledge of computer vision, graph neural networks, adversarial machine learning, and optimization techniques.
• Experience with Snowflake, PySpark, OneLake, SageMaker, Azure AI Services, and data visualization platforms.
• Professional experience in data science, machine learning, or AI engineering.
• Advanced proficiency in Python and SQL.
• Strong experience with PyTorch, TensorFlow, Scikit-learn, XGBoost, or comparable frameworks.
• Hands-on experience with statistical modeling, supervised and unsupervised learning, feature engineering, and model evaluation.
• Experience building production solutions using LLMs, NLP, RAG, embeddings, fine-tuning, and agentic AI frameworks.
• Experience with time-series forecasting methods such as Prophet, ARIMA, SARIMA, and gradient-boosting models.
• Experience deploying scalable ML pipelines using Kubernetes, Kubeflow, KServe, or equivalent technologies.
• Working knowledge of cloud AI and data services across Azure, AWS, or GCP.
• Experience with relational, analytical, graph, and vector databases.
• Strong problem-solving, stakeholder engagement, communication, and cross-functional collaboration skills.
• Master's degree in Data Science, Computer Science, Engineering, Statistics, Operations Research, or a related quantitative discipline.
