Develops data science solutions for Army space and missile defense mission analytics. Responsibilities include engineering datasets, building statistical and machine learning models, automating workflows, creating scripts and dashboards, debugging and refactoring Python code, supporting data governance, and communicating insights to stakeholders. The role requires transitioning prototypes into operational tools, collaborating with intelligence and technical teams, and maintaining secure, reproducible data pipelines.
Overview
Apogee is seeking a Data Scientist (DS) to support the U.S. Army Space and Missile Defense Command (USASMDC). This role applies data science, statistics, and automation to mission analytics, helping operational and intelligence teams process large, complex datasets and convert them into actionable insights in support of space and missile defense priorities.
The Data Scientist partners with analysts and technical stakeholders to identify high-value analytic problems, engineer and curate datasets, and develop reproducible pipelines and models to automate workflows and enrich mission data. Responsibilities include data exploration and feature engineering; building and evaluating statistical/ML approaches (as appropriate); developing scripts, tools, and dashboards to support analysis and reporting; and communicating results through clear documentation and briefings. The DS also supports data governance and quality efforts, ensures methods are transparent and repeatable, and transitions solutions into operational use in coordination with Government leads and mission users.
This is a full-time opportunity at Petterson Space Force Base (PSFB), CO.
****Contingent Upon Contract Award****
Responsibilities- Demonstrate experience and knowledge of computer science concepts, data architecture, intelligence practices, and managing data in a big-data environment.
- Demonstrate expert knowledge of Python, and Jupyter Notebooks and/or Jupyter Labs.
- Author cogent and logical scripts using Python and other applicable languages in a virtual environment using common Integrated Development Environments (IDE) such as VS Code, Spyder, PyScript, or Jupyter Notebooks.
- Develop and use advanced software programs, algorithms, query techniques, models to solve complex intelligence problems, and automated processes to normalize, integrate, and evaluate data.
- Debug existing and future Python code; refactor legacy code to ensure continued security, functionality, and compatibility.
- Document and block-comment all code to ensure recoverability and error-checking, and enhance reading, checking, and maintaining code in accordance with common data science and coding standards, such as PEP-8 for Python,5 or using style-guide features embedded in common IDE applications, such as Spyder, VS Code, PyScript or others upon approval by the Government.
- Collaborate across multi-discipline teams to ensure connectivity between various data sources and business problems.
- Identify meaningful insights, interpret, and communicate findings, plus make recommendations to stakeholders.
- Analyze requirements and evaluate technologies for data science capabilities including Natural Language Processing, Machine Learning, predictive modeling, statistical analysis, and hypothesis testing.
- Maintain awareness of emerging analytics and big-data technologies.
- Complete required course NSA NETA1400 (Technology Fundamentals for Analysis); recommended completion of any of the following NSA Courses: NETA2402/NETA2108 (Analysis II), RPTG2238, RPTG2235, RPTG3225, RPTG3222 (Basic Analytical Reporting) or equivalent curriculum.
- Complete recommended certifications: Data Science Council of America (DASCA) certifications, such as Associate Big Data Engineer (ABDE), Associate Big Data Analyst (ABDA), and Senior Data Scientist (SDS); Google Data Analytics Professional Certificate; IBM Data Science Professional Certification.
Minimum Experience:
Citizenship: Must be a US citizen Clearance: Must have and be able to maintain a Top Secret (TS) with Sensitive Compartmented Information (SCI) adjudicationEducation: Bachelors DegreeYears of Experience: 7+ years experience in data science/analytics engineering/software development in big-data environments.
Additional Experience:
- Expert Python skills; heavy use of Jupyter Notebooks/Labs and common IDEs (e.g., VS Code/Spyder).
- Proven ability to build and sustain automated data workflows (ingest/normalize/integrate/enrich/evaluate) using algorithms, queries, and models.
- Strong SDLC skills: debugging, refactoring legacy code, and maintaining secure/compatible codebases.
- Code quality discipline: clear documentation/block comments and adherence to PEP-8 (or equivalent style enforcement).
- Working knowledge of data architecture and ability to collaborate across multi-discipline teams to connect data sources to mission problems.
- Ability to communicate findings and recommendations to stakeholders.
- Experience applying/evaluating ML/NLP, predictive modeling, and statistical methods (hypothesis testing).
- NSA NETA1400 (Technology Fundamentals for Analysis) completion, or Government-approved equivalent.
Preferred Qualifications:Additional Experience:
- NSA courses: NETA2402/NETA2108 and/or RPTG2238/2235/3225/3222 (or equivalent).
- Certifications: DASCA (ABDE/ABDA/SDS), Google Data Analytics, and/or IBM Data Science.
- Experience transitioning prototypes into reusable, analyst-ready tools/pipelines and tracking emerging big-data/analytics tech.
Additional InformationLocation: Petterson Space Force Base (PSFB), COOn-siteTravel: 10%
Pay RangeUSD $155,000.00 - USD $190,000.00 /Yr.Similar Jobs
Aerospace • Artificial Intelligence • Hardware • Machine Learning • Software • Defense • Manufacturing
Build predictive failure models, real-time anomaly detection systems, diagnostic tools, and operational dashboards for spacecraft manufacturing, testing, and integration. Apply statistical modeling, causal inference, reliability analysis, and data mining to identify root causes, bottlenecks, quality issues, supplier risks, and process improvements. Develop reproducible Python and SQL analyses that support engineering decisions and mission reliability.
Top Skills:
ArimaIsolation ForestJupyterLstm AutoencodersMatplotlibNlpPandasProphetPythonScikit-LearnSmoteSQL
Aerospace • Artificial Intelligence • Hardware • Machine Learning • Software • Defense • Manufacturing
Build predictive models, anomaly detection systems, diagnostic tools, dashboards, and statistical quality-monitoring solutions for spacecraft manufacturing and testing. Analyze telemetry, production, supplier, and reliability data to identify failures, bottlenecks, delays, and root causes. Develop reproducible Python and SQL analyses and communicate actionable findings to engineering and operations stakeholders.
Top Skills:
ArimaIsolation ForestJupyter NotebooksLstm AutoencodersMatplotlibNlpPandasProphetPythonScikit-LearnSmoteSQL
Artificial Intelligence • Professional Services • Business Intelligence • Consulting • Cybersecurity • Generative AI
Leads teams in designing and deploying scalable AI and machine learning solutions for consulting clients. Responsibilities include data wrangling, complex analysis, data modeling, AI system implementation, data pipeline and infrastructure oversight, deep learning, neural networks, data quality validation, and stakeholder collaboration. The manager coaches team members, manages performance, supports innovation, and applies Python, Java, and cloud technologies to build production-ready AI applications.
Top Skills:
AWSCloud PlatformsData PipelinesDatabricksDeep LearningGCPJavaMachine Learning LibrariesAzureNatural Language Processing (Nlp)Neural NetworksPythonSnowflake
What you need to know about the Colorado Tech Scene
With a business-friendly climate and research universities like CU Boulder and Colorado State, Colorado has made a name for itself as a startup ecosystem. The state boasts a skilled workforce and high quality of life thanks to its affordable housing, vibrant cultural scene and unparalleled opportunities for outdoor recreation. Colorado is also home to the National Renewable Energy Laboratory, helping cement its status as a hub for renewable energy innovation.
Key Facts About Colorado Tech
- Number of Tech Workers: 260,000; 8.5% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Lockheed Martin, Century Link, Comcast, BAE Systems, Level 3
- Key Industries: Software, artificial intelligence, aerospace, e-commerce, fintech, healthtech
- Funding Landscape: $4.9 billion in VC funding in 2024 (Pitchbook)
- Notable Investors: Access Venture Partners, Ridgeline Ventures, Techstars, Blackhorn Ventures
- Research Centers and Universities: Colorado School of Mines, University of Colorado Boulder, University of Denver, Colorado State University, Mesa Laboratory, Space Science Institute, National Center for Atmospheric Research, National Renewable Energy Laboratory, Gottlieb Institute
