Job description

Overview What We’re Looking For As a Data Scientist at CyberPoint, you will develop advanced data science, machine learning and statistical solutions that help customers extract meaningful insights from complex datasets and support mission-critical decision making. You will work across the data science lifecycle, from exploring and understanding raw data to developing, evaluating and integrating analytics into production environments and analyst workflows. You will collaborate closely with subject matter experts to identify meaningful information within diverse datasets and translate manual analysis into automated repeatable analytics. You will develop and evaluate machine learning, statistical, heuristic and graph-based approaches, selecting and optimizing models based on appropriate performance metrics. You will also have opportunities to work with modern AI technologies, including Large Language Models, Retrieval-Augmented Generation and agentic workflows. When you become a part of CyberPoint, you are joining a dynamic, diverse, fast-growing company that welcomes creative thought and ambition. We're committed to creating an environment where each employee can thrive. What You'll Do • Develop machine learning, data mining, statistical, heuristic and graph-based algorithms to analyze complex datasets and solve mission-focused problems. • Explore and prototype multiple algorithms and approaches, selecting final models based on appropriate performance metrics and mission requirements. • Develop descriptive, predictive and prescriptive analytics to generate data-driven insights and recommendations. • Analyze diverse data sources and formats, including SQL tables, structured metadata, network logs and other mission-relevant datasets. • Work with subject matter experts (SMEs) to identify important information within raw data and translate domain knowledge into analytic requirements and features. • Develop scripts and data processing techniques to extract, transform and prepare information for analytic development. • Incorporate SME input into feature vectors suitable for machine learning development and testing. • Develop and optimize feature vectors for use in machine learning algorithms. • Develop experiments to collect data or create models to simulate data when suitable training or example data datasets are unavailable. • Identify appropriate algorithms for specific datasets and tune model and input parameters to improve performance. • Develop and implement statistical tests to support data-driven recommendations and decisions. • Evaluate and validate analytics using standard techniques and metrics such as cross-validation, ROC curves, confusion matrices and other appropriate measures. • Develop and optimize AI and machine learning models to address complex analytical problems. • Develop and optimize Large Language Models (LLMs) for natural language processing and information retrieval applications. • Implement prototype algorithms within production frameworks for integration into analyst workflows. • Generate reports and data visualizations that communicate dataset structure, findings and data-driven insights to customers and stakeholders. • Partner with SMEs and analysts to translate manual data analysis processes into automated analytic capabilities. • Utilize GPU-based computing resources to accelerate machine learning model training and deployment. • Contribute to the development and refinement of analytic development processes and best practices. • Oversee individual and analytic efforts and provide technical guidance to team members throughout the analytic development lifecycle. • Collaborate with software engineers, analysts, data scientists and mission stakeholders to transition analytic prototypes into operational capabilities. This position is 100% onsite and requires an active TS/SCI+FSP Security Clearance . Qualifications What You’ll Need • U.S. Citizenship. • Active TS/SCI Security Clearance with current full scope polygraph. • Bachelor's degree from an accredited college or university in a quantitative discipline such as Statistics, Mathematics, Operations Research, Engineering, Computer Science or a related field. • 5 years of experience analyzing datasets and developing analytics. • 5 years of experience programming with data analysis software such as Python, R, SAS or MATLAB. • An additional 4 years of experience in software development, cloud development, dataset analysis or developing descriptive, predictive and prescriptive analytics may be substituted for a Bachelor's degree. • A PhD from an accredited college or university in a quantitative discipline may be substituted for 4 years of experience. • Experience developing and evaluating machine learning, statistical, or heuristic models. • Experience developing feature vectors and preparing datasets for analytic or machine learning applications. • Experience evaluating analytic and machine learning model performance using appropriate statistical and performance metrics. • Experience working with subject matter experts to define analytic requirements and translate domain knowledge into data-driven solutions. • Experience producing data visualizations and reports that communicate meaningful insights from complex datasets. What Will Set You Apart • Experience with Large Language Models (LLMs). • Experience with Retrieval-Augmented Generation (RAG) frameworks. • Experience developing AI agents or agentic workflows. • Experience optimizing LLMs for natural language processing or information retrieval. • Experience using GPU-based computing resources for machine learning model training and deployment. • Experience integrating AI/ML prototypes into production systems and analyst workflows. • Experience with graph-based analytics or graph data. • Experience working with large-scale or highly diverse datasets. • Experience developing analytics within cloud environments. • Experience collaborating with Intelligence Community mission users or subject matter experts. Our Culture Great People, Exceptional Benefits Great people are the foundation of any great company. To attract and retain great people, CyberPoint offers fulfilling work that we like to balance with the rest of life. We accomplish this by offering outstanding benefits that allow each of our employees to live and work well. To learn more, cyberpointllc.com . Be a part of CyberPoint. Be valued. We are an inclusive community in which all types of diversity are embraced, respected and seen as true value for the company. We are committed to cultivating this community, but we realize there is still more work to do. CyberPoint will continue to evolve into a more inclusive and equitable company and is fully committed to the principles of equal employment opportunity and affirmative action. CyberPoint is an Equal Opportunity Employer and does not discriminate against any employee or applicant for employment because of gender, gender identity or expression, sexual orientation, race, age, religion, physical or mental disability, veterans' status or other federal, state and local protected characteristics. As a federal contractor, CyberPoint has established affirmative action programs to ensure non-discrimination and affirmative action in CyberPoint's policies and practices for qualified women, minorities, protected veterans, and individuals with disabilities. The narrative portion of CyberPoint's affirmative action plans are available for inspection at our offices during normal business hours. Employees and applicants interested in inspecting these plans should contact Human Resources by phone 410-779-6700 or by email at hr@cyberpointllc.com for assistance. If you are interested in applying for employment with CyberPoint and need special assistance or an accommodation to apply for a posted position, contact our Human Resources department by email at hr@cyberpointllc.com or by calling 410-779-6700.

Requirements

Must-haves

What We’re Looking For
When you become a part of CyberPoint, you are joining a dynamic, diverse, fast-growing company that welcomes creative thought and ambition. We're committed to creating an environment where each employee can thrive.
Develop machine learning, data mining, statistical, heuristic and graph-based algorithms to analyze complex datasets and solve mission-focused problems.
Explore and prototype multiple algorithms and approaches, selecting final models based on appropriate performance metrics and mission requirements.
Develop descriptive, predictive and prescriptive analytics to generate data-driven insights and recommendations.
Analyze diverse data sources and formats, including SQL tables, structured metadata, network logs and other mission-relevant datasets.
Work with subject matter experts (SMEs) to identify important information within raw data and translate domain knowledge into analytic requirements and features.
Develop scripts and data processing techniques to extract, transform and prepare information for analytic development.
Incorporate SME input into feature vectors suitable for machine learning development and testing.
Develop and optimize feature vectors for use in machine learning algorithms.
Develop experiments to collect data or create models to simulate data when suitable training or example data datasets are unavailable.
Identify appropriate algorithms for specific datasets and tune model and input parameters to improve performance.
Develop and implement statistical tests to support data-driven recommendations and decisions.
Evaluate and validate analytics using standard techniques and metrics such as cross-validation, ROC curves, confusion matrices and other appropriate measures.
Develop and optimize AI and machine learning models to address complex analytical problems.
Develop and optimize Large Language Models (LLMs) for natural language processing and information retrieval applications.
Implement prototype algorithms within production frameworks for integration into analyst workflows.
Generate reports and data visualizations that communicate dataset structure, findings and data-driven insights to customers and stakeholders.
Partner with SMEs and analysts to translate manual data analysis processes into automated analytic capabilities.
Utilize GPU-based computing resources to accelerate machine learning model training and deployment.
Contribute to the development and refinement of analytic development processes and best practices.
Oversee individual and analytic efforts and provide technical guidance to team members throughout the analytic development lifecycle.
Collaborate with software engineers, analysts, data scientists and mission stakeholders to transition analytic prototypes into operational capabilities.
This position is 100% onsite and requires an active TS/SCI+FSP Security Clearance .

Nice-to-haves

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Keywords to mirror

machine learningaisqlpythonmlrest

Platform: bullhorn
Effort: medium