Data Scientist (II-Senior), Manufacturing Analytics

Location: Fully onsite in Denver, Colorado, or Long Beach, California; candidates must be based in or able to commute to an office daily.

Base salary: $125,000–$270,000 per year, plus equity and benefits.

Company

hirify.global develops autonomous spacecraft, advanced payloads, mission software, and space-based interceptors for U.S. and allied space-security missions.

What you will do

• Build predictive models using manufacturing telemetry, test data, and reliability records to identify component failures before they affect missions.
• Design and deploy real-time anomaly detection and quality-monitoring systems for launch operations, environmental testing, and spacecraft integration.
• Perform root cause analysis on schedule delays, test failures, and quality issues using causal inference, data mining, and statistical modeling.
• Develop diagnostic systems that combine manufacturing history, supplier data, test logs, and failure reports to accelerate troubleshooting.
• Build operational dashboards and mine production and test data to identify bottlenecks, failure patterns, process risks, and improvement priorities.
• Write maintainable Python and SQL code and reproducible Jupyter notebooks while collaborating with operations, manufacturing, and reliability engineers.

Requirements

• Bachelor’s degree in data science, statistics, industrial engineering, applied mathematics, operations research, or a related quantitative field with 2–4 years of experience, or a relevant master’s degree with no experience required.
• Proficiency in Python, including pandas, scikit-learn, and matplotlib, and in SQL for data manipulation, analysis, and visualization.
• Strong statistical knowledge covering hypothesis testing, regression, time-series analysis, survival analysis, and experimental design.
• Experience building end-to-end data pipelines covering data cleaning, feature engineering, model training, validation, and deployment.
• Ability to communicate technical findings through clear visualizations and actionable recommendations.
• Must satisfy U.S. Government space-technology export requirements: U.S. citizenship, U.S. lawful permanent residence, protected-individual status, or eligibility to obtain the required authorizations.

Nice to have

• Reliability engineering experience, including Weibull or Cox models, reliability growth modeling, and failure mode analysis.
• Manufacturing analytics experience with statistical process control, multivariate control charts, or quality prediction.
• Experience with anomaly detection, time-series forecasting, causal inference, imbalanced classification, operations research, or discrete-event simulation.
• Experience applying text mining or NLP to log analysis, failure-report clustering, or automated fault diagnosis.

Culture & Benefits

• Equity and benefits including health, dental, vision, HRA/HSA options, paid time off, and paid holidays.
• 401(k) and parental leave.
• Work alongside operations, manufacturing, reliability, and engineering teams on high-stakes spacecraft systems.
• Daily in-office work in Denver or Long Beach in a manufacturing and testing environment that may involve varying temperature, noise, indoor or outdoor conditions, bending, sitting, lifting, and driving.