Aerospace, Defense, Space Technology, SaaS

Data Scientist (II-Senior), Manufacturing Analytics

Denver, COOnsiteInternship$125,000–$270,000 /yrPosted 2 months ago

Is this role right for you?

Upload your resume and get a skill-by-skill breakdown — see exactly where you match, where you're close, and what to highlight. Not a mystery percentage.

Get a tailored resume highlighting what this role needs.

Required skills

manufacturing telemetry
predictive models
anomaly detection
root cause analysis
Python
SQL
pandas
scikit-learn
matplotlib
hypothesis testing

Nice to have

reliability engineering
Weibull
Cox models
failure mode analysis
statistical process control
SPC

Role summary

We are seeking a Data Scientist (II-Senior) specializing in Manufacturing Analytics to join our team. In this role, you will develop predictive models to anticipate component failures, deploy real-time anomaly detection systems, and conduct data-driven root cause analysis for schedule and quality issues. Your work will involve mining historical data to optimize processes, score supplier reliability, and predict delivery delays. You will also build diagnostic tools that integrate various data sources to accelerate troubleshooting and create operational dashboards for real-time awareness. The ideal candidate will have a strong foundation in Python, SQL, and statistical modeling, with experience in data pipelines and communicating technical findings. Experience in reliability engineering, manufacturing analytics, and causal inference is preferred. This is a fully onsite role.

Space is a warfighting domain. True Anomaly seeks those with the talent and ambition to build the technology that secures it.

OUR MISSION

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.

OUR VALUES

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.

BENEFITS & PERKS*

Best-in-class healthcare: 100% company-paid medical, dental, and vision coverage for you and your dependents, with HSA/HRA options

Generous time off: Flexible Time Off (FTO) for exempt employees, accrued PTO of up to 25 days for non-exempt employees, plus 12 paid holidays; Parental Leave; Sick Leave

Fuel for your day: Daily catered lunch and unlimited snacks for in-office employees

And more: 401(k) retirement plan, fitness reimbursement, and Dog Fridays

Equity participation: Equity is included as part of our total compensation package, giving you an opportunity to share in the company’s success.

*Do not apply to fixed term and temporary roles

YOUR MISSION

You'll build predictive models that catch component failures before they impact missions by analyzing manufacturing telemetry, deploy real-time anomaly detection systems for testing and operations that flag deviations operators would miss, and investigate schedule slips and quality issues using data-driven root cause analysis to distinguish signal from noise. You'll mine historical production data to identify bottlenecks, optimize test durations, and reduce rework, while scoring supplier reliability and predicting delivery delays to flag at-risk components. Throughout, you'll develop integrated diagnostic tools that fuse logs, telemetry, and historical data to narrow failure root causes and accelerate engineering investigations that keep spacecraft on schedule and missions on track.

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

QUALIFICATIONS

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

PREFERRED SKILLS AND EXPERIENCE

Experience with reliability engineering: survival analysis (Weibull, Cox models), reliability growth modeling, failure mode analysis

Familiarity with manufacturing analytics: statistical process control (SPC), multivariate control charts, quality prediction from process data

Exposure to anomaly detection techniques: Isolation Forest, LSTM autoencoders, change point detection, multivariate process monitoring

Internship, research, or project experience in operations analytics, supply chain forecasting, or industrial IoT telemetry analysis

Understanding of causal inference methods: directed acyclic graphs (DAGs), counterfactual reasoning, confounding variable analysis

Experience with imbalanced classification: SMOTE, cost-sensitive learning, active learning for rare event prediction

Familiarity with time-series forecasting: ARIMA, Prophet, exponential smoothing, handling regime changes and structural breaks

Coursework or project work in operations research, queuing theory, optimization, or discrete event simulation

Experience with text mining and NLP for log analysis, failure report clustering, or automated fault diagnosis

COMPENSATION

Base Salary: $125,000 - 270,000

Equity + Benefits including Health, Dental, Vision, HRA/HSA options, PTO and paid holidays, 401K, Parental Leave

Your actual level and base salary will be determined on a case-by-case basis and may vary based on the following considerations: job-related knowledge and skills, education, location, and experience.

ADDITIONAL REQUIREMENTS

Work Location—this is a fully onsite role. Candidates must be based in or able to commute to our Denver or Long Beach office daily.

Work environment—the work environment; temperature, noise level, inside or outside, or other factors that will affect the person's working conditions while performing the job.

Physical demands—the physical demands of the job, including bending, sitting, lifting and driving.

This position will be open until it is successfully filled. To submit your application, please follow the directions below. #LI-Onsite

To conform to U.S. Government space technology export regulations, including the International Traffic in Arms Regulations (ITAR) you 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.

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 know.

To protect candidates and our company from application fraud and impersonation, we use third-party tools to verify applicant identity and detect fraudulent applications. Learn more in our Privacy Notice.

Ready to apply?

You'll be redirected to True Anomaly's application page.

Data Scientist (II-Senior), Manufacturing Analytics

Is this role right for you?

Required skills

Nice to have

Role summary

Similar roles

See how RiseMe works