Lead Data Scientist

- Bachelors degree in computer science, Data Science, AI, Statistics, or a related field. - Advanced degrees or relevant certifications are advantageous. - 5+ years of experience in data science, focusing on end-to-end AI/ML solutions in a business context. - Proven history of developing and launching ML models and GenAI applications. - Strong collaborative experience in large organizations across different functions. - Practical knowledge of ML frameworks (TensorFlow, PyTorch, Scikit-learn) and cloud-based AI services (AWS, Azure, GCP). - Proficiency in exploratory data analysis (EDA), feature engineering, experimental design, and model development. - Proficient in programming languages such as Python or R for data analysis and machine learning model creation. - Extensive knowledge of supervised and unsupervised learning techniques, including classical machine learning, time series analysis, and NLP. - Hands-on experience with large language models (LLMs) such as GPT, Claude, or LLaMA, including fine-tuning and prompt engineering. - Expertise in retrieval-augmented generation (RAG) with vector databases like FAISS or Pinecone. - Familiarity with GenAI frameworks such as LangChain or LlamaIndex for enterprise applications. - Experience utilizing cloud-based AI platforms (Azure OpenAI, AWS Bedrock, Google Vertex AI) for scalable deployment. - Understanding of model evaluation techniques and standards to ensure accuracy, reliability, and compliance. - Familiarity with MLOps practices for maintaining long-term model performance, including deployment, monitoring, and retraining. - Excellent communication and stakeholder management skills, capable of explaining complex technical concepts clearly. - Strong problem-solving skills with a proactive, results-oriented approach. - Ability to thrive in a fast-paced, matrixed organization with cross-functional teamwork.