AI Data Scientist

System One; McLean (VA); Remote; USD 120,000 - 180,000; Full time

Benefits offered by this job

Health and welfare benefits

401(k) plan

Job summary

System One is seeking an AI Data Scientist to define and deliver AI/use cases from McLean, VA, in a remote setting. The role emphasizes ML, NLP, and productionizing models across structured and unstructured data, enabling enhanced search, discovery, and analytics.

You will partner with stakeholders to translate business needs into scalable data science solutions, build NLP and semantic search capabilities, and collaborate with engineers to deploy models on cloud platforms, APIs, and batch

Qualifications

• Bachelor’s or Master’s degree in a relevant field.
• 4+ years of data science, ML, or analytics experience.
• Strong Python proficiency and SQL skills.
• Experience with NLP, semantic search, entity resolution.
• Experience with large-scale structured and unstructured data.

Responsibilities

• Define and deliver AI/use cases with stakeholders.
• Develop ML models for search, discovery, and insights.
• Build NLP, semantic search, and entity resolution capabilities.
• Leverage OCR/ICR data for downstream analytics and search.
• Integrate models into production via APIs and pipelines.
• Collaborate with data engineers to productionize models.
• Create evaluation frameworks and explainability methods.
• Support analytics dashboards and operational insights.
• Participate in Agile sprints and client-facing efforts.
• Communicate findings to technical and non-technical audiences.

Education

Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field

Tools

Palantir Foundry

Databricks

Spark

AWS

Job description

System One is seeking an AI Data Scientist to define and deliver AI and analytics use cases in a remote setting from McLean, Virginia. The role focuses on machine learning and NLP capabilities, integrating models into production, and enabling search, discovery, and analytics across structured and unstructured data.

Key Responsibilities

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

Required Qualifications

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

Technologies

• Python, Pandas, Scikit-learn, PyTorch, TensorFlow
• SQL
• Databricks, Spark
• AWS cloud services, AWS S3
• Palantir Foundry

Benefits

• Health and welfare benefits coverage options including medical, dental, vision, spending accounts, life insurance, and voluntary plans
• 401(k) plan participation

What Would Be Nice To Have

• Experience working with Palantir Foundry and/or Palantir AIP, especially for 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 such as AWS SageMaker or Databricks Machine Learning for model development, deployment, and lifecycle management.
• Experience developing explainable AI (XAI) solutions, including confidence scoring and traceability.
• 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.