Lead Data Scientist

Key Responsibilities Lead end-to-end data science projects, from problem definition to production deployment. Develop and optimize machine learning, deep learning, and statistical models. Design and implement Generative AI, LLM, and RAG-based solutions where applicable. Translate complex business problems into analytical and predictive solutions. Establish best practices for experimentation, model validation, explainability, and monitoring. Mentor data scientists and review technical deliverables. Partner with engineering, product, and business stakeholders. Drive MLOps practices, model governance, scalability, and responsible AI. Present analytical insights and recommendations to senior leadership. Required Qualifications Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Engineering, or a related field. 10 years of experience in data science, machine learning, or advanced analytics, depending on the organization. Strong proficiency in Python, SQL, and libraries such as pandas, scikit-learn, PyTorch, or TensorFlow. Expertise in supervised and unsupervised learning, feature engineering, model evaluation, and statistical methods. Experience deploying models using cloud platforms such as AWS, Azure, or GCP. Knowledge of ML pipelines, Docker, Kubernetes, CI/CD, and model monitoring. Strong communication, stakeholder management, and technical leadership skills. Strong hands-on experience building predictive machine learning models, recommender systems, ranking models, and prescriptive optimization models Strong proficiency in Python, SQL, MLOps, and modern AI/ML development frameworks (Scikit-learn, TensorFlow, PyTorch, Hugging Face, AWS Sagemaker, etc.) Skills: ml,machine learning,data science,aws,leadership,sql,data,artificial intelligence,data models,python #J-18808-Ljbffr