Senior Data Scientist

This position requires an active U.S. national security clearance and the ability to obtain one. To learn more about the security clearance process please access this link. Additionally, travel may be required to customer and subcontractor sites as well as other office locations. Accelint is a mission-driven technology company focused on strengthening national security and supporting critical industries . We build the technologies that help operators and organizations see what’s happening, make faster and better decisions, take action with confidence, and stay ready for what comes next. Our work includes advanced sensors, autonomous systems, mission command and control software, AI-enabled training and simulation, and tools that improve logistics, maintenance, and overall readiness. For nearly 30 years we have supported military and civilian agencies across the Department of Defense, U.S. allies and partners, and essential industries. When you join Accelint, your work directly contributes to protecting national security and strengthening the systems our society depends on. The Senior Data Scientist is responsible for designing, developing, testing, and maintaining software applications to provide advanced analytics for software and edge solutions team. This role focuses on developing innovative solutions driven by exploratory data analysis from complex and high-dimensional datasets. The Senior Data Scientist will apply knowledge of statistics, machine learning, programming, and data modeling. They use a flexible, analytical approach to design, develop, and evaluate predictive models and advanced algorithms to mine the stores of big data. They generate and test hypotheses and analyze and interpret the results of product experiments. Create data visualizations, dashboards, and reports to communicate findings. This role will involve applying AI/ML techniques to read and process technical data to include CAD models for ingestion into enterprise systems. The Senior Data Scientist will work with product engineers to translate prototypes into new products, services, and features and provide guidelines for large-scale implementation. This role will require collaboration with other data scientists and software engineers to implement algorithms and provide insights to end users. The ideal candidate has at least 5 years of experience in data science, with a demonstrated ability to collaborate with cross-functional teams. Duties And Responsibilities Lead the design, development, and implementation of statistical techniques and algorithms. Write clean, maintainable, and efficient code, and ensure best practices in coding standards. Test algorithms against key benchmarks and implement techniques to enhance performance. Work with developers, solution architects, and DevSecOps engineers to incorporate algorithms within software architectures and effectively deploy the algorithms within existing code base. Work with engineers to incorporate prototype algorithms into new products, services, and features and provide guidelines for large-scale implementation. Research and identify areas for applications of AI/ML in support of the program. Work with the development team and government teams to align AI/ML efforts. Prepare and maintain comprehensive technical documentation related to algorithm development. Ensure accuracy and completeness of all documentation. Mentor junior data scientist and coordinate activities to complete key data science tasks Foster effective collaboration with cross-functional teams to achieve project objectives. Communicate complex technical information clearly and effectively. Utilize advanced software development tools and methodologies to support project requirements. Integrate software development tools and methodologies into the workflow to improve efficiency and accuracy. Required Qualifications Bachelor's degree in Computer Science, Statistics, Mathematics, Engineering, or related quantitative field. At least 5 plus years of experience in data science or related discipline. Experience analyzing system performance data and time series data. Proficiency in Python and its data science libraries (Pandas, NumPy, Scikit-learn, etc.). Strong background in statistical analysis, forecasting techniques, and anomaly detection Experience with SQL and relational databases. Knowledge of data visualization tools for creating operational dashboards (Tableau, Power BI, Grafana, or similar). Understanding of machine learning fundamentals with a willingness to expand AI/ML implementation skills. Excellent problem-solving and analytical skill