About Careertakes

👉 Important disclosure: Careertakes is a third-party recruiting platform supporting this hiring process. If selected, you will be employed directly by our client, Scientific & QA.

Applicants for this role may also receive access to additional matched opportunities through the Careertakes platform.

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What You’ll Do

You will work as an entry-level data scientist supporting hardware production and spacecraft operations for a confidential client in the Scientific & QA industry. Your analysis will turn manufacturing and mission telemetry into actionable insights — surfacing production bottlenecks, identifying root causes of test failures, training predictive models to flag at-risk components, and monitoring on-orbit health to detect degradations before they impact missions.

• Perform exploratory data analysis on manufacturing telemetry, test logs, mission data, and on-orbit spacecraft health telemetry to identify patterns and surface anomalies
• Build operational dashboards (Grafana, Plotly Dash, or similar) to show real-time production status, spacecraft health metrics, mission performance, and anomaly alerts
• Train and validate basic predictive models (logistic regression, random forests) to flag at-risk components and predict spacecraft health degradation
• Write SQL queries to extract, join, and aggregate data from manufacturing databases, test systems, mission telemetry streams, and archives
• Analyze test failures and on-orbit anomalies to identify common failure modes, cluster similar issues, and quantify schedule/mission impact
• Create clear visualizations (matplotlib, seaborn, Plotly) for engineers, manufacturing leads, mission operators, and program managers
• Implement statistical process control charts to detect out-of-spec manufacturing conditions and telemetry trends before they cascade
• Monitor telemetry streams for anomalies such as battery voltage trends, thermal behavior, attitude control health, and communications link quality
• Document analysis methodology and results in Jupyter notebooks to enable reproducibility and handoff
• Learn and apply reliability engineering and mission operations concepts: failure modes, burn-in testing, on-orbit commissioning, spacecraft health monitoring, and anomaly response

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Qualifications

• Bachelor’s or Master’s degree in data science, statistics, industrial engineering, applied mathematics, operations research, or a related quantitative field
• Proficiency in Python for data analysis (pandas, numpy, matplotlib, seaborn)
• Working knowledge of SQL for querying relational databases (SELECT, JOIN, GROUP BY, aggregation)
• Coursework or demonstrable understanding of statistics: hypothesis testing, regression, probability distributions, experimental design
• Ability to produce clear visualizations that communicate findings to both technical and non-technical audiences
• Strong curiosity about failure modes and how data can predict problems before they occur
• Debugging mindset and attention to data quality and reproducibility
• Eagerness to learn manufacturing, operations, and reliability engineering domains
• U.S. Citizen (required for facility access and government contracts)

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Preferred Skills & Experience

• Experience with machine learning in Python (scikit-learn), model validation, cross-validation
• Familiarity with time-series analysis and sensor data techniques (trend plotting, change-point detection, smoothing)
• Exposure to dashboarding and visualization tools (Grafana, Plotly Dash, Tableau)
• Understanding of reliability concepts (failure rates, survival analysis, MTBF)
• Prior internship or project work with operational/manufacturing/IoT data
• Version control experience (git) and collaborative data workflows
• Experience cleaning/wrangling real-world telemetry: handling missing values, outliers, and noisy signals
• Familiarity with anomaly detection methods (z-scores, control charts, isolation techniques)
• Comfort writing reproducible analyses in Jupyter notebooks

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Compensation

• Base salary (Federal Heights / Denver area estimate): $75,000 per year (estimated)
• This is a 3-month temporary employment engagement with potential for conversion to regular employment based on performance and business need.

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Work Location & Additional Requirements

• Location: Onsite / hybrid near Federal Heights / Denver / Colorado Springs — successful candidates will be located near Denver or Colorado Springs and must be able to work on-site as required
• Physical demands: role may include typical lab/manufacturing/office conditions; may involve sitting, standing, occasional lifting, and site-specific safety protocols
• Security/export rules: to conform to U.S. government space-technology export regulations (including ITAR), you must be a U.S. citizen, lawful permanent resident, protected individual as defined by 8 U.S.C. 1324b(a)(3), or otherwise eligible to obtain required authorizations from the U.S. Department of State
• This position requires facility access consistent with government contract requirements

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Equal Opportunity & Hiring Transparency

Careertakes and our client are Equal Opportunity Employers committed to building a diverse and inclusive workforce. We prohibit discrimination or harassment of any kind. To support a fair and efficient hiring process, AI tools may be used to assist with application review or resume screening. These tools do not replace human decision-making. Final hiring decisions are made by people.

If you have questions about how your data is used, please contact us directly.