Lead Data Scientist
- Saxon Global Inc.
4 Hours Ago
NA
W2
Charlotte NC-NC, Columbus-NC, Dallas-TX
3-10 Years
Required Skills: GCP, Azure cloud, AI, ML, AWS Sagemaker, Lambda, S3, Athena, Python , Spark
Job Description
- Master’s Degree, PhD is preferred
- 3+ years of professional applied mathematics (e.g. statistics, economics, quantitative development/analysis, actuarial, mathematical modeling, etc.)
- Strong experience in Python or R
- AWS (preferred) or GCP or Azure cloud experience
- Experience building AI / ML solutions: end-to-end ownership, practical implementation
- Generative AI familiarity (how AI models and tools work, exposure to RAG architectures, GenAI solution patterns)
- Curiosity and passion for applying AI to solve business problems
- Collaborate with the Product Owner to manage the end to end AI development lifecycle—requirements gathering, data sourcing, model development, proof of concept demonstrations, risk governance reviews, and production deployment across both on premises and AWS environments.
• Demonstrate strong self-discipline and professional ownership in managing project activities, maintaining transparent communication with leadership, seeking managerial guidance when appropriate, and proactively surfacing risks, blockers, or resource needs to ensure timely delivery.
• Apply automation techniques to streamline manual processes, enhance productivity and accuracy, and develop reusable, scalable self service tools and assets.
• Stay current with emerging machine learning, cloud, and AI technologies, driving innovation by evaluating and integrating new capabilities into existing workflows and products.
Basic Requirements
• PhD or Master’s degree in Statistics, Economics, Data Science, or related field.
• Three to Five years related work experience in AWS cloud machine learning or a similar AI platforms, with familiarity in AWS Sagemaker, Lambda, S3, Athena, etc.
• Proficiency in one or more programming languages, including Python (preferred) or R, Spark, and other modern data science tools.
• Working knowledge of Large Language Models (Llama, Claude, Titan), including experience with frameworks such as LangChain, vector databases, embeddings, and prompt engineering.
Preferred Skills and Characteristics
• Willingness to step outside traditional modeling tasks to solve broader technical or business challenges in support of team and organizational goals.
• Hands on experience with LLM fine tuning
• Practical understanding of advanced Retrieval Augmented Generation (RAG) methods such as MMR, multi vector retrieval, RAG fusion, HYDE, self RAG, and retrieval evaluation frameworks.
• Knowledge and practical experience with Agentic AI and agentic workflows, including task orchestration, multi agent collaboration, tool use agents, and workflow automation patterns.
• Hands on experience with advanced AWS AI/ML services such as Bedrock, JumpStart, Textract, and related ML orchestration capabilities.
