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