Data Scientist

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

• 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.

• 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.

ing outsourced services and workforce solutions across North America. We help clients get work done more efficiently and economically, without compromising quality. System One not only serves as a valued partner for our clients, but we offer 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.


System One is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, age, national origin, disability, family care or medical leave status, genetic information, veteran status, marital status, or any other characteristic protected by applicable federal, state, or local law.

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