Job Requirements
Remote
Public Trust Polygraph not specified
Mid Level Career (5+ yrs experience)
$113,000 - $188,000
Job Description
Job Title: Data Scientist
Location: McLean, VA
Type: Contract To Hire
Compensation: Not specified
Work Model: Remote
Hours: 40.0
Clearance: Must be eligible to obtain a US Public Trust
Contact: Crystal.dinnocenti@systemone.com
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.
REQUIREMENTS
• 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, 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.
Location: McLean, VA
Type: Contract To Hire
Compensation: Not specified
Work Model: Remote
Hours: 40.0
Clearance: Must be eligible to obtain a US Public Trust
Contact: Crystal.dinnocenti@systemone.com
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.
REQUIREMENTS
• 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, 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.
group id: 10295162
