Leidos' Defense Systems, Weapons Sensors, Advanced Sensors and Protective Technologies Portfolio is seeking a talented Mid-Level Data Analyst to function full-time within the Advanced Sensors and Protective Technologies Portfolio. You will join a diverse team of software developers, engineers, and scientists to help create unique solutions for complex problems. Our team solves important problems that make a difference and support our customers in the current and future defense of our nation; primarily in the areas of modeling & simulation (M&S) , sensor integration & characterization, data analysis, algorithm development, and testing for electro-optical infrared (EO/IR) systems. Candidate will be expected to execute within the Agile/Scrum framework to develop analysis tools and data products, productively contribute to a team environment, and communicate effectively with management, coworkers, and customers Primary Responsibilities. • Work closely with a team of engineers and scientists to develop analysis scripts, data processing pipelines, and data products. • Assist with data collections to include cleaning and validating data collected from multiple sources. • Analyze data to identify trends, patterns, and insights that support program objectives. • Develop data visualizations to support analysis products. • Collaborate with cross-functional teams to understand data needs and provide input into SW, M&S, and test plan development. • Implement industry standard and custom performance metrics. • Document analysis methodologies, processes, and findings. • Assist with design of experiments (DoE) and conducting parametric trade studies. • Enhance current M&S capabilities to narrow gap between real and synthetic data. • Conduct exploratory data analysis. Basic Qualifications. • Bachelor's degree from an accredited university in data science, mathematics, computer science, or an equivalent engineering or science degree with relevant analysis-related experience plus 4-8 years of experience in a related field or Master's degree from an accredited university in data science, mathematics, computer science, or an equivalent engineering or science degree, or an equivalent engineering or science degree with relevant software-related experience plus 2-6 years of experience in a related field. • Intermediate ability in Python with familiarity using statistical and data analysis libraries (NumPy, SciPy, Pandas, scikit-image, statsmodels, etc.) and data visualization libraries (matplotlib, seaborn, plotly, etc). • Experience analyzing large datasets containing mixed data types. • Proficiency developing data visualization products. • Knowledge of a variety of ML architectures to include classical ML techniques as well as modern deep learning (DL) architectures for supervised and unsupervised learning. • Candidate must be a resident of the North Alabama area or willing to relocate to the Huntsville - North Alabama, AL area. • Active SECRET clearance or above. Preferred Qualifications. • Experience evaluating or developing computer vision algorithms for object detection, recognition, and tracking. • Experience with evaluating or developing machine learning solutions. • Knowledge of statistical analysis techniques for performing exploratory data analysis, comparing distributions of data, and for performing low dimensional embedding. • Familiarity or interest in EO/IR phenomenology and experience with image processing. • Familiarity with C++ programming. Original Posting: July 20, 2026 For U.S. Positions: While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above. Pay Range: Pay Range $87,100.00 - $157,450.00 The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.