Note: The job is a remote job and is open to candidates in USA. System One provides technical outsourced services, workforce solutions, staffing, and recruiting for technology, government, and other critical sectors. The AI Data Scientist will develop and deploy machine learning, NLP, semantic search, and entity resolution solutions across structured and unstructured data, while supporting analytics, dashboards, model evaluation, and stakeholder communication.
Responsibilities
- 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
Skills
- 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
- U.S. Citizenship required and 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)
- 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
- 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
Benefits
- Eligible employees health and welfare benefits coverage options including medical, dental, vision, spending accounts, life insurance, voluntary plans, as well as participation in a 401(k) plan.
Company Overview