Description
Overview
Systems Planning and Analysis, Inc. (SPA) delivers high-impact, technical solutions to complex national security issues. With over 50 years of business expertise and consistent growth, we are known for continuous innovation for our government customers, in both the US and abroad. Our exceptionally talented team is highly collaborative in spirit and practice, producing Results that Matter. Come work with the best! We offer opportunity, unique challenges, and clear-sighted commitment to the mission. SPA: Objective. Responsive. Trusted.
The Space and Intelligence Division provides professional services to the US Space Force, Combatant Commands, Intelligence Community, and NASA. Our work includes enterprise architectural assessments, systems engineering and integration, test, planning and execution, cost estimating and analysis, acquisition support, and cybersecurity. We are trusted partners developing approaches and concepts to meet emerging high priority needs, assessing cutting-edge technologies, and supporting capabilities for our National Defense. Come join the fastest growing Division at Systems Planning and Analysis, Inc.!
The Space Systems Group (SSG), part of SPA's Space and Intelligence Division, provides timely and objective assessments and recommendations integrating technical, operational, programmatic, policy and business analysis. We focus on our key clients in the Space community including the US Space Force's Space Systems Command (USSF/SSC), one of the three designated Field Commands under USSF. We work tirelessly to provide integrated solutions based on information and communications throughout the chain of command. We provide clear and consistent analysis and recommendations which are aligned to strategic and leadership goals while balancing the ability to execute on time and on budget within the technical communities. Come join an organization responsible for being a key enabler of Spacepower!
SPA has a near-term need for a Data Scientist - Junior/Journeyman.
Responsibilities
The Junior/Journeyman Data Scientist supports the development, refinement, and validation of predictive sustainment capabilities. This role applies data analytics, reliability analysis, and model development to improve operational availability, identify degradation trends, and support sustainment decision‑making. The Data Scientist works with engineering, logistics, and operations teams to leverage Government‑furnished data, validated threat/architecture outputs, and SBIR-derived analytics tools to produce repeatable, data-driven sustainment insights.
Key Responsibilities
- Develop, maintain, and refine predictive analytics models supporting sustainment of space mission systems.
- Analyze operational data, maintenance records, telemetry streams, reliability metrics, and system performance trends to identify degradation or failure indicators.
- Support the development of predictive maintenance models, reliability assessments, and CBM+ analytical products under senior guidance.
- Prepare and validate data pipelines, feature engineering workflows, and model QA steps to ensure analytical accuracy and repeatability.
- Assist with development of failure mode analyses, lifecycle performance studies, and sustainment risk assessments.
- Apply supervised and unsupervised ML techniques—where permitted—to support anomaly detection, maintenance forecasting, and reliability trend identification.
- Produce clear analytical summaries, technical findings, sustainment metrics, and decision-support products for program management and engineering reviews.
- Maintain configuration-controlled analytical artifacts and contribute to sustainment baselines supporting TO Task 5 deliverables.
- Coordinate with cross-functional teams to ensure data fidelity, traceability, and compliance with sustainment frameworks.
Qualifications
Required Qualifications
- US Citizenship with TS/SCI clearance at time of application with ability to obtain and maintain SAP clearance
- Bachelor's degree in Data Science, Engineering, Applied Mathematics, Computer Science, Analytics, or related field
- Experience with Python, R, or similar analytics tools
- Experience working with datasets, metrics, or basic statistical/ML techniques
- Strong analytical skills, problem-solving abilities, and documentation proficiency
- Ability to report to designated work location in Colorado Springs, up to full time, based on the needs of the customer
Desired Qualifications
- Experience with reliability engineering concepts (FMEA, FRACAS, RCM, probability of failure models)
- Exposure to predictive maintenance modeling, CBM+, or digital sustainment environments
- Experience with analytics visualization tools (Power BI, Tableau)
- Familiarity with AI/ML modeling, feature engineering, or anomaly detection workflows
- Experience with defense systems, sustainment programs, or engineering teams
- Relevant early-career certifications (e.g., CompTIA Data+, AWS Practitioner, beginner reliability certs)
Pay Range Information
At SPA, we strive to deliver a robust total compensation package that will attract and retain top talent. Elements of the compensation package include competitive base pay and variable compensation opportunities. SPA provides eligible employees with an opportunity to enroll in a variety of benefit programs, generally including health insurance, flexible spending accounts, health savings accounts, retirement savings plans, life and disability insurance programs, and a number of programs that provide for both paid and unpaid time away from work. The specific programs and options available to any given employee may vary depending on eligibility factors such as geographic location, date of hire, etc. Please note that the salary information shown below is a general guideline only. Salaries are commensurate with experience and qualifications, as well as market and business considerations. Colorado, Pay Transparency Salary range: USD $100,000.00/Yr. - USD $150,000.00/Yr.
Qualifications
Required Qualifications
- US Citizenship with TS/SCI clearance at time of application with ability to obtain and maintain SAP clearance
- Bachelor's degree in Data Science, Engineering, Applied Mathematics, Computer Science, Analytics, or related field
- Experience with Python, R, or similar analytics tools
- Experience working with datasets, metrics, or basic statistical/ML techniques
- Strong analytical skills, problem-solving abilities, and documentation proficiency
- Ability to report to designated work location in Colorado Springs, up to full time, based on the needs of the customer
Desired Qualifications
- Experience with reliability engineering concepts (FMEA, FRACAS, RCM, probability of failure models)
- Exposure to predictive maintenance modeling, CBM+, or digital sustainment environments
- Experience with analytics visualization tools (Power BI, Tableau)
- Familiarity with AI/ML modeling, feature engineering, or anomaly detection workflows
- Experience with defense systems, sustainment programs, or engineering teams
- Relevant early-career certifications (e.g., CompTIA Data+, AWS Practitioner, beginner reliability certs)
Responsibilities
The Junior/Journeyman Data Scientist supports the development, refinement, and validation of predictive sustainment capabilities. This role applies data analytics, reliability analysis, and model development to improve operational availability, identify degradation trends, and support sustainment decision‑making. The Data Scientist works with engineering, logistics, and operations teams to leverage Government‑furnished data, validated threat/architecture outputs, and SBIR-derived analytics tools to produce repeatable, data-driven sustainment insights.
Key Responsibilities
- Develop, maintain, and refine predictive analytics models supporting sustainment of space mission systems.
- Analyze operational data, maintenance records, telemetry streams, reliability metrics, and system performance trends to identify degradation or failure indicators.
- Support the development of predictive maintenance models, reliability assessments, and CBM+ analytical products under senior guidance.
- Prepare and validate data pipelines, feature engineering workflows, and model QA steps to ensure analytical accuracy and repeatability.
- Assist with development of failure mode analyses, lifecycle performance studies, and sustainment risk assessments.
- Apply supervised and unsupervised ML techniques—where permitted—to support anomaly detection, maintenance forecasting, and reliability trend identification.
- Produce clear analytical summaries, technical findings, sustainment metrics, and decision-support products for program management and engineering reviews.
- Maintain configuration-controlled analytical artifacts and contribute to sustainment baselines supporting TO Task 5 deliverables.
- Coordinate with cross-functional teams to ensure data fidelity, traceability, and compliance with sustainment frameworks.
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