Machine Learning/Data Scientist

Responsibilities

• Design and implement machine learning and advanced analytics solutions to address operational and strategic questions.
• Collaborate with stakeholders to define analytical problems and translate business needs into modeling requirements.
• Prepare and engineer features from multiple data sources to ensure data quality and suitability for modeling.
• Develop, train, and validate models including classification, regression, clustering, and forecasting.
• Evaluate model performance, perform error analysis, and refine approaches to improve accuracy and interpretability.
• Integrate model outputs into dashboards, applications, or automated workflows.
• Document modeling approaches and communicate findings through clear narratives and visualizations for non-technical audiences.

Requirements

• Bachelor's degree in Data Science, Statistics, Computer Science, Mathematics, or a closely related field.
• 5+ years of experience in data science, machine learning, or advanced analytics roles.
• Demonstrated experience developing, validating, and deploying machine learning models using Python or R.
• Strong background in statistics, model evaluation, and experimental design.
• Experience with data preparation, feature engineering, and working with complex, multi-source datasets.

Preferred Qualifications

• Master's degree in a quantitative field.
• Familiarity with integrating model outputs into BI tools or applications via APIs or embedded analytics.
• Experience working within mission-oriented or public sector environments (e.g., DHS, DoD).

Benefits

• Medical, dental, and vision insurance.
• Paid time off and holidays.
• Employee Stock Ownership Plan (ESOP).
• 401(k) retirement plan.
• Life insurance.
• Flexible work schedules.

About the Company

Parsons is a digitally enabled solutions provider focused on creating the future of the defense, intelligence, and critical infrastructure markets. From Earth to outer space, we deliver tomorrow’s solutions today through an agile, innovative, and disruptive approach.