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: [email protected] 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.
Ref: #851-Rockville-S1
