Data Scientist (FORECASTED)

This position is contingent on contract award.

About the role

Columbia Technology Partners is seeking Data Scientists to develop advanced analytics, machine learning models, and data-driven solutions that transform complex datasets into actionable insights. The ideal candidate will leverage statistical analysis, machine learning, data mining, and visualization techniques to support mission objectives while collaborating with subject matter experts, engineers, and stakeholders to automate analytical workflows and deliver production-ready analytic capabilities.

Responsibilities

• Develop machine learning, statistical, graph-based, and heuristic algorithms to analyze complex datasets.
• Produce data visualizations that provide insight into data structure, trends, and operational relevance.
• Collaborate with Subject Matter Experts (SMEs) to identify valuable information within raw data sources and develop extraction methodologies.
• Transform customer objectives and analytical processes into quantitative models and software-based solutions.
• Develop descriptive, predictive, and prescriptive analytics to support decision-making and mission outcomes.
• Design and execute statistical tests to support data-driven recommendations and conclusions.
• Create feature vectors and datasets suitable for analytics development, testing, and model training.
• Generate reports, visualizations, and presentations that communicate findings and recommendations to stakeholders.
• Partner with software engineers and technical teams to integrate analytical capabilities into operational workflows.
• Implement prototype analytics and machine learning models within production environments.
• Develop experiments and modeling approaches to generate or simulate training data when operational datasets are unavailable.
• Identify, evaluate, and select appropriate machine learning algorithms for specific datasets and mission requirements.
• Tune models and optimize performance using established validation techniques and performance metrics.
• Evaluate analytic approaches and provide recommendations throughout the analytics development lifecycle.
• Design analytics that scale effectively across large datasets and distributed environments.
• Develop and train machine learning systems supporting automation and advanced mission capabilities.
• Apply advanced validation techniques including cross-validation, ROC analysis, confusion matrices, and other performance assessment methodologies.

Qualifications

• Bachelor's degree in Statistics, Mathematics, Operations Research, Engineering, Computer Science, or a related discipline from an accredited college or university.
• A Master's degree in a related discipline may be substituted for two (2) years of relevant analytics experience and one (1) year of programming experience.
• A PhD in a related discipline may be substituted for four (4) years of relevant analytics experience for Level 2 candidates.
• Four (4) additional years of relevant experience may be substituted in lieu of a bachelor's degree.
• Level 1: Four (4) years of experience analyzing datasets and developing analytics,