Sr Staff / Senior Scientific Data Analyst

SciTec•Boulder, CO

21h•Onsite

About The Position

SciTec, a wholly owned subsidiary of Firefly Aerospace, is a dynamic non-traditional defense contractor that delivers advanced technologies in support of U.S. National Security and Defense. For the past forty-five plus years, we have supported Department of Defense customers by developing innovative remote sensing algorithms, tools, and techniques to deliver world-class data exploitation capabilities supporting missile defense; intelligence, surveillance, & reconnaissance; space domain awareness; and aircraft survivability missions. Important Notice: SciTec exclusively works on U.S. government contracts that require U.S. citizenship for all employees. SciTec cannot sponsor or assume sponsorship of employee work visas of any type. Further, U.S. citizenship is a requirement to obtain and keep a security clearance. Applicants that do not meet these requirements will not be considered. We are seeking a highly skilled Sr Staff / Senior Scientific Data Analyst to join our analytics team supporting an innovative Missile Defense Agency (MDA) program from our Boulder, CO office. This role blends advanced data analysis with hands‑on scientific computing and simulation development, contributing directly to mission‑critical decision support. The analyst will work with large‑scale simulations of current and future systems, design and troubleshoot experiment configurations, and evaluate whether system behaviors align with expected operational outcomes. They will also develop Python‑based tools to automate analysis workflows, interpret complex performance data, and generate insights that inform new operational paradigms and validate existing ones.

Requirements

Bachelor’s degree in Computer Science, Engineering, Mathematics, Physical Sciences, or another quantitative field
6+ years of professional experience in data analysis, scientific computing, simulation development, or related technical roles
Strong proficiency in Python, including writing, debugging, and extending medium‑to‑large codebases
Experience developing and maintaining data processing pipelines, including ingestion, cleaning, transformation, and validation of diverse datasets
Hands-on experience with scientific computing libraries, such as NumPy, SciPy, Pandas, and Matplotlib
Demonstrated ability to design, run, and troubleshoot simulation or algorithm‑evaluation experiments
Experience creating clear, reproducible visualizations and communicating analytical findings
Professional experience working in Linux environments
Proficiency with Git and collaborative development workflows
Ability to work independently with minimal oversight and collaborate across technical teams
Excellent written and verbal communication skills
Ability to work in person at the Boulder, CO office
Ability to obtain and maintain a DoD security clearance

Nice To Haves

Advanced degree (MS or PhD) in a quantitative or scientific discipline
Experience working with scientific, remotely sensed, or experimental data
Background in algorithm performance evaluation, numerical methods, or computational modeling
Experience developing custom analysis tools, simulation utilities, or experiment frameworks in Python
Familiarity with messaging and communication technologies such as Protocol Buffers (protobuf), ZeroMQ, Kafka, gRPC, or REST APIs
Experience with DevOps or CI/CD tools, such as Docker, Podman, Jenkins, or GitLab CI/CD
Experience with Agile processes and tools, such as Jira
Active DoD security clearance

Responsibilities

Ingest, clean, and transform diverse structured and unstructured datasets
Develop Python-based data readers, preprocessing pipelines, and visualization tools
Design and compute new metrics to evaluate algorithm, system, or experiment performance
Interpret raw and graphical performance data into actionable insights for engineering and scientific teams
Create clear, formal analysis reports and present findings to technical and non‑technical audiences
Design, configure, and troubleshoot simulation experiments for scientific or algorithmic evaluation
Modify, extend, and maintain existing Python simulation tools with minimal oversight
Develop novel Python code to support new experiment types or analysis workflows
Perform regular demos of experiments and results for cross-training and feedback
Work independently to scope, execute, and deliver complex analytical tasks
Collaborate across engineering, research, and product teams to share findings and refine methodologies
Mentor junior analysts and engineers in best practices for data processing, visualization, and experimental design
Participate in peer review of analysis methods, code, and reports
Contribute to documentation, knowledge sharing, and clear technical communication
Work as part of an indisciplinary Agile team
Other duties as assigned