Data Scientist/AI Lead

Program Management Solutions LLC

Rockville, MD, United States

23 days ago

Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Experience required

5 years minimum

Working hours

Regular working hours

Job source

www.indeed.com

Tech stack

Application Programming Interfaces (APIs) Artificial Intelligence Data Analysis Microsoft Azure Health Informatics Data Architecture Information Engineering Data Governance Data Infrastructure Graph Database Information Lifecycle Management Interoperability

+21 more

Knowledge Management Machine Learning Meta-Data Management Scientific Computating Search Technologies Systems Integration Enterprise Search High Performance Computing Feature Engineering Data Ingestion Large Language Models Prompt Engineering Model Validation Generative AI Information Technology Deployment Automation HuggingFace Performance Monitor Machine Learning Operations Software Version Control Automation Anywhere

Requirements

Bachelor’s degree in Data Science, Computer Science, Artificial Intelligence, Machine Learning, Bioinformatics, Biomedical Informatics, Computational Biology, Engineering, or related field.
Minimum 10+ years of experience supporting data science, artificial intelligence, machine learning, informatics, analytics, data engineering, or scientific computing initiatives.
Minimum 5+ years of experience leading technical teams supporting data-intensive, AIenabled, or scientific computing environments.
Experience designing and implementing data architectures, ingestion pipelines, metadata management, and data governance frameworks.
Experience supporting FAIR data principles, data harmonization, interoperability, and scientific data lifecycle management.
Experience developing, integrating, or supporting AI/ML-enabled analytics, predictive modeling, automation, or advanced computational workflows.
Experience designing, deploying, or supporting Generative AI (GenAI) solutions, including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), intelligent assistants, AI agents, prompt engineering, and enterprise knowledge management solutions.
Experience supporting responsible AI practices, including model documentation, transparency, explainability, performance monitoring, and bias identification or mitigation.
Experience supporting cloud, high-performance computing, GPU-enabled, or large-scale analytics platforms.
Experience implementing Machine Learning Operations (MLOps) practices including model lifecycle management, model registries, feature engineering pipelines, automated retraining, version control, deployment automation, and continuous model monitoring.
Experience supporting vector databases, semantic search, knowledge graphs, embeddings, enterprise search, and AI-enabled knowledge management platforms.
Experience briefing technical and executive stakeholders.

Preferences

Master’s degree or higher in a related field.
Experience supporting NIH, HHS, or biomedical research organizations.
Experience with bioinformatics, cheminformatics, knowledge graphs, ontology management, and translational science data environments.
Experience supporting AI-enabled analytics, machine learning operations, advanced scientific computing, high-content imaging, or large-scale biomedical data environments.
Experience with human-in-the-loop AI workflows, image segmentation, model validation, or AI-enabled scientific platform integration.
Experience supporting enterprise Generative AI platforms using Azure OpenAI, Amazon Bedrock, Google Vertex AI, OpenAI APIs, Hugging Face, LangChain, Semantic Kernel, or equivalent technologies.
Experience supporting AI governance, AI security, prompt management, model evaluation, AI red teaming, or enterprise AI adoption initiatives.
Experience integrating GenAI capabilities into scientific research, biomedical informatics, or decision-support environments.