Summary: Seeking a Lead Data Science Engineer to deliver production-grade AI/ML solutions on AWS for optimization and forecasting in the energy sector, leading multiple engagements. Highlights: 1. Lead design, development, and deployment of AI/ML solutions on Amazon SageMaker 2. Apply Amazon Bedrock to deliver generative AI solutions 3. Lead multiple parallel client engagements We are seeking a **Lead Data Science Engineer** to deliver production\-grade AI/ML solutions on AWS for optimization and forecasting in the energy (oil \& gas) sector while leading multiple engagements in parallel. You will combine hands\-on ML engineering with stakeholder leadership to ship cloud\-native outcomes—apply now to help clients realize measurable value from AI. **Responsibilities** * Lead design, development, and deployment of optimization and forecasting models on Amazon SageMaker * Build end\-to\-end ML workflows including data preparation, feature engineering, training, evaluation, and inference * Architect scalable, cost\-efficient, production\-ready inference solutions aligned to AWS best practices * Apply Amazon Bedrock to deliver generative AI solutions for document processing, knowledge extraction, and automation * Drive technical decisions across workstreams and provide escalation support for AI/ML topics * Coordinate delivery across multiple parallel engagements while managing priorities and timelines * Collaborate with client data teams, domain experts, and AWS Professional Services to align solutions to business goals * Implement monitoring, logging, and model governance using AWS\-native tooling * Apply AWS Well\-Architected Framework principles with focus on security, reliability, performance, and cost optimization * Document model architectures, pipeline configurations, and operational procedures for maintainability * Deliver knowledge transfer sessions and produce handover materials to enable client self\-sufficiency **Requirements** * 5\+ years of experience in data science and machine learning delivery * Experience with Amazon SageMaker for training, hosting, and pipelines * Experience building optimization and forecasting models * Proven leadership experience leading multiple parallel client engagements * Strong stakeholder management skills with executive\-level communication * Deep AWS cloud\-native best practices knowledge for production AI/ML solutions * Hands\-on MLOps skills across data preparation, feature engineering, evaluation, and inference * Advanced energy domain experience in oil \& gas or industrial AI/ML use cases * Strong problem\-solving skills with ability to operate independently across workstreams * Upper\-Intermediate English proficiency (B2, Upper\-Intermediate) **Nice to have** * Amazon Lookout experience for anomaly detection on industrial or operational data