Senior Data Scientist - Predictive Analytics for Space Missions

True Anomaly, Inc.; Denver (CO); On-site; USD 110,000 - 160,000; Full time

Benefits offered by this job

100% health coverage (medical, dental,

Flexible time off

Daily catered lunch

401(k) retirement plan

Equity participation

Job summary

True Anomaly, Inc. seeks a data scientist to build predictive models that catch component failures by analyzing manufacturing telemetry and historical reliability data.

You will deploy real-time anomaly detection for testing and operations, and perform root cause analysis to identify actionable improvements. Join a team that fuses logs, telemetry, and history to accelerate investigations and keep spacecraft programs on schedule.

Qualifications

• Bachelor’s degree in data science or related field, plus 2–4 years of experience; or a Master’s with no experience.
• Proficient in Python (pandas, scikit-learn, matplotlib) and SQL for data manipulation, analysis, and visualization
• Strong statistical fundamentals: hypothesis testing, regression, time-series, 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 can drive decisions

Responsibilities

• Build predictive models for component failure prediction using manufacturing telemetry, test data, and historical reliability records.
• Design and deploy anomaly detection systems for launch operations, environmental testing, and spacecraft integration.
• Perform root cause analysis on schedule delays, test failures, and quality escapes using causal inference and data mining.
• Develop data-driven diagnostic systems that fuse manufacturing history, supplier data, test logs, and failure reports to narrow root causes.
• 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.
• 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

Time-series

Hypothesis testing

Data pipelines

Data visualization

Communication

Education

Bachelor’s in data science / related field

Master’s in data science / related field

Tools

Jupyter

Job description

True Anomaly, Inc. seeks a data scientist to build predictive models that catch component failures by analyzing manufacturing telemetry and historical reliability data.

You will deploy real-time anomaly detection for testing and operations, and perform root cause analysis to identify actionable improvements. Join a team that fuses logs, telemetry, and history to accelerate investigations and keep spacecraft programs on schedule.