Spacecraft Reliability Data Scientist, Predictive Analytics

True Anomaly; Long Beach (CA); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Healthcare

Generous time off

Equity

401k and Roth 401k

Learning & Development

Job summary

True Anomaly is seeking a data scientist to build predictive models using manufacturing telemetry, test data, and reliability records. You will deploy real-time anomaly detection for testing and operations, and investigate root causes of failures and schedule slips using causal inference and data mining.

The role emphasizes end-to-end data pipelines, clear visualizations for non-technical stakeholders, and collaboration with operations, manufacturing, and reliability engineers to drive

Qualifications

• Bachelor’s in data science, statistics, industrial engineering, applied mathematics, operations research, or similar quantitative discipline.
• 2–4 years of experience; or a Master’s degree with no experience required.
• Eagerness to learn manufacturing, operations, and reliability engineering domains where data science drives operational improvements.
• Strong statistics fundamentals: hypothesis testing, regression, time-series analysis, survival analysis, experimental design.

Responsibilities

• Build predictive models using manufacturing telemetry, test data, and historical reliability records.
• Design and deploy anomaly detection systems for launch operations and testing.
• Perform root cause analysis on schedule delays and quality issues using data-driven approaches.
• Develop data pipelines: cleaning, feature engineering, model training, validation, deployment.
• Create real-time dashboards for production, test, and integration workflows.

Skills

Python

SQL

Statistics

Time-series

Data Visualization

Communication

Education

Bachelor's degree in quantitative field

Master’s degree in quantitative field

Tools

Pandas

scikit-learn

Matplotlib

SQL

Job description

True Anomaly is seeking a data scientist to build predictive models using manufacturing telemetry, test data, and reliability records. You will deploy real-time anomaly detection for testing and operations, and investigate root causes of failures and schedule slips using causal inference and data mining.

The role emphasizes end-to-end data pipelines, clear visualizations for non-technical stakeholders, and collaboration with operations, manufacturing, and reliability engineers to drive