Data Scientist

• Data Scientist (ML & AI Modeling) – (Focus - ML) • Ideally, has a PhD (must have master's at a minimum) • Any Status • Hybrid: 3-days/week onsite • Position will run thru Fiscal Year End (April 2026) w/ a possible extension • ONE 60-minute MS Teams interview • Need one photo ID, please Responsibilities: As a data scientist, you will use expertise in modeling, data engineering, and building applications with LLMs. Your responsibilities will span a wide range of data science activities, such as those listed below: 1. Collaborate with users to deliver big data and machine learning models and AI/LLM solutions. 1. Use AI/ML to empower business with novel capabilities such as automating workflows by utilizing 1. machine learning and LLM systems. 1. Research and analyze complex data sets, combine different sources and types of data to develop 1. machine learning and deep learning models making value out of data. 1. Design and implement efficient, adaptable, scalable, and reliable pipelines and algorithms to process 1. unstructured and structured data. 1. Implement new statistical or other mathematical methodologies as needed for specific models or 1. analysis. 1. Leverage or build cloud-based technologies and solutions to deliver optimized ML models at scale. 1. Prototype solutions and conduct experiments highlighting results and lessons learned. 1. Provide technical expertise and guidance to users on AI/ML and LLM best practices. 1. Help the users evaluate the AI/ML solution from a technical perspective. 1. Leverage industry knowledge and stay close to latest technology trends 1. Contribute to the development of sample applications, tutorials, presentations and training material for 1. big data and machine learning technologies. Qualifications: • Master's or Ph.D. in Computer Science, Data Science, or related field, plus a minimum of four years of • relevant professional experience or a master degree. • A strong background in machine learning algorithms, natural language processing and LLMs. • Proficiency in programming languages, including SQL, R, Python, Java, and MATLAB. • Demonstrated work experience with prompt engineering, retrieval augmented generation • architectures and LangChain/LangGraph or similar tools and frameworks. • Demonstrated work experience with extract, transform, and load (ETL) for large‐scale, complex • data sets. • Demonstrated work experience with structured/unstructured data and parallel/distributed • computation (PySpark). • Knowledge of cloud technologies and services (Microsoft Azure, AWS, etc.). • Knowledge of network configuration, information risk and security guidelines. • Knowledge of version control systems, software configuration management and source code • lifecycle management tools. • Knowledge of data architecture and application architecture, target state design and strategy. • Ability to research and identify innovative approaches for data acquisition, as well as new uses for • existing datasets. • Ability to effectively leverage knowledge, skills, tools, and techniques in managing complex • programs and projects, ensuring alignment with defined business, technical, and security • requirements. • Ability to research, design, develop, implement and manage applications based on specific • business needs