Lead Data Scientist

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.

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