Space-Ready Data Scientist, Manufacturing Analytics

True Anomaly; City of Long Beach (NY); On-site; USD 125,000 - 270,000; Full time

Benefits offered by this job

Health, Dental, Vision

401K

Paid time off

Parental Leave

Job summary

True Anomaly seeks a data scientist to build predictive models that catch component failures before they impact missions. You’ll analyze manufacturing telemetry, deploy real-time anomaly detection systems for testing and operations, and perform data-driven root-cause analysis to keep spacecraft on schedule.

You’ll mine historical production data to identify bottlenecks, optimize test durations, and assess supplier reliability to flag at-risk components.

Qualifications

• Proficiency in Python and SQL for data manipulation, analysis, and visualization.
• Strong statistical fundamentals: hypothesis testing, regression, time-series analysis, and experimental design.
• Experience building end-to-end data pipelines: cleaning, feature engineering, model training, validation, and deployment.

Responsibilities

• Build predictive models for component failure prediction using manufacturing telemetry, test data, and historical reliability records to catch issues before they impact missions.
• Design and deploy anomaly detection systems for launch operations, environmental testing, and spacecraft integration that flag deviations in real-time without overwhelming operators with false alarms.
• Perform root cause analysis on schedule delays, test failures, and quality escapes using causal inference, data mining, and statistical modeling to identify actionable improvement opportunities.
• Develop data-driven diagnostic systems that fuse manufacturing history, supplier data, test logs, and failure reports to narrow root causes and accelerate troubleshooting.
• Build and maintain operational dashboards providing real-time situational awareness across production, test, and integration workflows.
• Mine historical test and production data to identify patterns, cluster failure modes, prioritize process improvements, and quantify risk for upcoming builds.
• Implement statistical process control and quality monitoring systems that detect out-of-spec conditions before they propagate downstream.
• Write clear, maintainable Python/SQL code and Jupyter notebooks that document analysis methodology and enable reproducibility across the engineering team.
• Learn and grow alongside operations, manufacturing, and reliability engineers, translating business questions into data solutions that drive decisions

Skills

Python

SQL

Statistics

Data pipelines

Communication

Education

Bachelor's degree in data science / related field

Master's degree in related field with no experience required

Tools

Pandas

scikit-learn

Matplotlib

Job description

True Anomaly seeks a data scientist to build predictive models that catch component failures before they impact missions. You’ll analyze manufacturing telemetry, deploy real-time anomaly detection systems for testing and operations, and perform data-driven root-cause analysis to keep spacecraft on schedule.

You’ll mine historical production data to identify bottlenecks, optimize test durations, and assess supplier reliability to flag at-risk components.