AI/ML Data Scientist

Government Agency/Program: HHS/GS ( Guidehouse )

Position: AI/ML Data Scientist

JO ID: JO000280494

Clearance: (Public Trust Eligible)

Temp to Perm/Direct Hire/ Long-Term Consultant: Temp to Perm

Notes: Need to be a data Scientist that has AI/ML experience; building AI-enabled search solutions, developing explainable AI (XAI) solutions and experience developing and applying machine learning models

What You Will Do :

• Partner with stakeholders to define and deliver AI/analytics use cases, translating business needs into scalable data science solutions.
• Design and develop machine learning models and analytical approaches to support search, discovery, and insight generation across structured and unstructured data.
• Build and implement NLP, semantic search, and entity resolution capabilities to enable advanced information retrieval and relationship analysis.
• Leverage document-based data (e.g., OCR/ICR outputs, metadata, and free text) to extract insights and support downstream analytics and search solutions.
• Collaborate with data engineers to integrate models into production environments, including Palantir Foundry, Databricks, and AWS-based platforms.
• Develop model evaluation frameworks, confidence scoring, and explainability approaches to ensure transparency and usability of AI outputs.
• Support development of analytics, reporting, and dashboards to drive operational insights and decision-making.
• Operate within an Agile delivery model, contributing to sprint planning, experimentation, and iterative solution delivery.
• Communicate findings and recommendations clearly to both technical and non-technical audiences, including client stakeholders.
• Contribute to solution design, proposal support, and thought leadership in AI/analytics capabilities.

What You Will Need :

• Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or related field.
• A minimum of 4 years of experience in data science, machine learning, or applied analytics roles
• Ability to obtain and maintain a Public Trust clearance.
• Experience developing and applying machine learning models, including:
  • Natural Language Processing (NLP)
  • Semantic search or information retrieval
  • Entity resolution or relationship modeling
• Experience working with large-scale structured and unstructured data, particularly document-based datasets (e.g., text, PDFs, images).
• Experience leveraging metadata and extracted features to support analytics and modeling.
• Strong proficiency in Python for data science and machine learning (e.g., Pandas, Scikit-learn, PyTorch or TensorFlow) and solid SQL skills.
• Experience working with Databricks and/or Spark-based environments for scalable data processing.
• Familiarity with AWS cloud services for data access, processing, or model deployment.
• Experience working with data lake or lakehouse architectures (e.g., AWS S3, Databricks), including querying and transforming large-scale datasets.
• Experience integrating models into production environments (e.g., APIs, batch pipelines, or embedded analytics platforms).
• Understanding of model evaluation, validation, and performance metrics.
• Strong communication skills and ability to translate analytical outputs into actionable insights.
• Experience working in cross-functional, matrixed teams in an Agile environment.

What Would Be Nice To Have :

• Experience working with Palantir Foundry and/or Palantir AIP, particularly in support of AI-enabled search or analytics workflows.
• Consulting experience strongly preferred
• Experience building AI-enabled search solutions, including semantic search, document retrieval, and ranking models.
• Experience with multimodal data processing, including text and image-based analytics.
• Familiarity with OCR/ICR pipelines and document intelligence use cases.
• Experience with enterprise ML platforms (e.g., AWS SageMaker, Databricks Machine Learning) for model development, deployment, and lifecycle management.
• Experience developing explainable AI (XAI) solutions, including confidence scoring and traceability of results.
• Experience designing analytics dashboards or reporting solutions for end users.
• Previous experience supporting federal clients or working in regulated environments.
• Experience in a consulting firm and/or client-facing delivery role.
• Experience supporting training, user enablement, or scaling analytics capabilities across teams.

Familiarity with graph-based analytics, ontology-driven models, or relationship mapping