Data Scientist (II-Senior), Manufacturing Analytics at True Anomaly | CA, US | Rezi

Data Scientist (II-Senior), Manufacturing Analytics at True Anomaly

Data Scientist (II-Senior), Manufacturing Analytics

True Anomaly · CA, US

3 weeks ago

Data Scientist (II-Senior), Manufacturing Analytics

True Anomaly · CA, US

21 days ago
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About the Role

True Anomaly delivers decisive capabilities for space superiority by building autonomous spacecraft, advanced payloads, mission software, and space-based interceptors. This role is crucial in developing technology that secures the space environment and counters threats.

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.

Requirements

  • Bachelor's degree in data science, statistics, industrial engineering, applied mathematics, operations research, or a similar quantitative discipline, plus 2-4 years of experience; or a Master's degree in one of these fields with no experience required.
  • Proficient in Python (pandas, scikit-learn, matplotlib) and SQL for data manipulation, analysis, and visualization.
  • Strong statistical fundamentals: hypothesis testing, regression, time-series analysis, survival analysis, and experimental design.
  • Experience building end-to-end data pipelines: data cleaning, feature engineering, model training, validation, and deployment.
  • Ability to communicate technical findings to non-technical stakeholders through clear visualizations and actionable recommendations.
  • Eagerness to learn manufacturing, operations, and reliability engineering domains where data science drives real operational improvements.
  • Passion for spaceflight and building reliable systems that perform in high-stakes environments.
  • Must be a U.S. citizen, lawful permanent resident of the U.S., protected individual as defined by 8 U.S.C. 1324b(a)(3), or eligible to obtain the required authorizations from the U.S. Department of State.

Skills

  • Python
  • SQL
  • pandas
  • scikit-learn
  • matplotlib
  • Hypothesis testing
  • Regression
  • Time-series analysis
  • Survival analysis
  • Experimental design
  • Data cleaning
  • Feature engineering
  • Model training
  • Model validation
  • Model deployment
  • Data visualization
  • Reliability engineering
  • Survival analysis (Weibull, Cox models)
  • Reliability growth modeling
  • Failure mode analysis
  • Manufacturing analytics
  • Statistical process control (SPC)
  • Multivariate control charts
  • Quality prediction from process data
  • Anomaly detection techniques
  • Isolation Forest
  • LSTM autoencoders
  • Change point detection
  • Multivariate process monitoring
  • Operations analytics
  • Supply chain forecasting
  • Industrial IoT telemetry analysis
  • Causal inference methods
  • Directed acyclic graphs (DAGs)
  • Counterfactual reasoning
  • Confounding variable analysis
  • Imbalanced classification
  • SMOTE
  • Cost-sensitive learning
  • Active learning for rare event prediction
  • Time-series forecasting
  • ARIMA
  • Prophet
  • Exponential smoothing
  • Operations research
  • Queuing theory
  • Optimization
  • Discrete event simulation
  • Text mining
  • NLP

Location

  • Denver
  • Long Beach

Work Type

  • Onsite
  • Fully onsite

Experience Level

  • 2-4 years of experience

Education Level

  • Bachelor's degree
  • Master's degree

Salary/Compensations

  • $125,000 - $270,000

Benefits

  • Equity
  • Health
  • Dental
  • Vision
  • HRA/HSA options
  • PTO
  • Paid holidays
  • 401K
  • Parental Leave

About the Company

  • True Anomaly delivers decisive capabilities for space superiority.
  • We build autonomous spacecraft, advanced payloads, mission software, and space-based interceptors — enabling the U.S. and its Allies to secure the space environment and counter threats from the ultimate high ground.
  • Be the offset. We create asymmetric advantages with creativity and ingenuity.
  • What would it take? We challenge assumptions to deliver ambitious results.
  • It’s the people. Our team is our competitive advantage and we are better together.

Equal Opportunity

  • True Anomaly is committed to equal employment opportunity on any basis protected by applicable state and federal laws.
  • If you have a disability or additional need that requires accommodation, please do not hesitate to let us.