Data Scientist/AI Lead

Program Management Solutions LLC
Rockville, United States of America
5 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior

Job location

Rockville, United States of America

Tech stack

API
Artificial Intelligence
Data analysis
Azure
Health Informatics
Data Architecture
Information Engineering
Data Governance
Data Infrastructure
Graph Database
Information Lifecycle Management
Interoperability
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.

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