Data Scientist with a Focus on Policy

at  Riverside Research Institute

Riverside Overview: Riverside Research is an independent National Security Nonprofit dedicated to research and development in the national interest. We provide high-end technical services, research and development, and prototype solutions to some of the country’s most challenging technical problems. All Riverside Research opportunities require U.S. Citizenship. Position Overview:
Riverside Research is seeking a Data Scientist with a focus on Policy to join our team in Washington, D.C. This role will play a pivotal part in bridging the gap between data analysis and data governance within the NGA Analysis Directorate. The ideal candidate will leverage data science techniques to enhance data policy compliance, improve data quality, and ensure robust data governance practices, supporting NGA’s mission of leading Geospatial Intelligence (GEOINT) analytic capabilities.

Responsibilities:

• Policy Development: Develop and implement data management policies and standards to ensure compliance with legal and regulatory requirements.
• Data Analysis: Conduct data analysis to support policy compliance and data governance initiatives.
• Statistical Modeling: Develop and apply statistical models to monitor and enhance data governance practices.
• Data Quality Improvement: Evaluate and improve data quality, usability, and availability.
• Machine Learning: Implement machine learning models to automate data governance tasks and policy enforcement.
• Data Governance: Collaborate with Data Stewards to develop and refine data governance policies and procedures.
• Security Management: Ensure the application of appropriate security controls to protect data integrity and confidentiality.
• Training and Advocacy: Train staff on data management best practices and the application of data science to policy enforcement.
• Performance Improvement: Identify and document data-related performance improvements, providing mission-focused justifications and integrating solutions to enhance operations.
• Technical Support: Provide technical support for customer engagement, training, coordination with analysts and scientists, and hosting technical exchange meetings.

Qualifications:

Required:

• 8 years relevant experience
• Experience in data analysis, statistical modeling, and machine learning.
• Strong understanding of data governance, data quality, and policy compliance.
• Proficiency in data science tools and programming languages (e.g., Python, R).
• Excellent communication and collaboration skills.
• Active TS/SCI security clearance required.

Desired:

• Bachelors degree in Data Science, Computer Science, Statistics, or a related field and 5 years relevant experience

Global Comp: $110,000 - $140,000 This represents the typical compensation range for this position based on experience, location and other factors. Closing Statement: Riverside Research Institute is a not-for-profit, technology-oriented defense company, where service to our customers and support of our staff is our overall mission. Riverside is an affirmative action-equal opportunity employer and complies with all applicable federal, state, and local laws regarding recruitment and hiring. Riverside offers comprehensive compensation and benefit packages to our employees. Riverside bases its employment decisions solely on technical experience, qualifications and other job-related criteria related to our organizational purpose as a not-for-profit company, and without regard to race, color, religion, age, sex marital status, sexual orientation, national origin, physical or mental disability, veteran’s status or any other status legally protected by applicable federal, state, and local law

• Policy Development: Develop and implement data management policies and standards to ensure compliance with legal and regulatory requirements.
• Data Analysis: Conduct data analysis to support policy compliance and data governance initiatives.
• Statistical Modeling: Develop and apply statistical models to monitor and enhance data governance practices.
• Data Quality Improvement: Evaluate and improve data quality, usability, and availability.
• Machine Learning: Implement machine learning models to automate data governance tasks and policy enforcement.
• Data Governance: Collaborate with Data Stewards to develop and refine data governance policies and procedures.
• Security Management: Ensure the application of appropriate security controls to protect data integrity and confidentiality.
• Training and Advocacy: Train staff on data management best practices and the application of data science to policy enforcement.
• Performance Improvement: Identify and document data-related performance improvements, providing mission-focused justifications and integrating solutions to enhance operations.
• Technical Support: Provide technical support for customer engagement, training, coordination with analysts and scientists, and hosting technical exchange meetings