Data Scientist - Manufacturing Analytics

Hadrian — Manufacturing the Future

Hadrian is building autonomous factories that help aerospace and defense companies manufacture rockets, satellites, jets, and ships up to 10x faster and up to 2x cheaper. By combining advanced software, robotics, and full-stack manufacturing, we are reinventing how America produces its most critical parts.

We recently raised $260 million dollar Series C to accelerate this mission. We are excited to be launching a new Factory in Mesa, Arizona, a 270,000 square foot facility that will create 350 new jobs immediately. We are opening a new headquarters to support thousands of future hires, launching Hadrian Maritime to serve naval production, and introducing a Factory-as-a-Service model that delivers complete systems instead of individual parts.

Hadrian works with startups, Tier 1 and Tier 2 suppliers, and major defense contractors across space, shipbuilding, and aviation to scale production, reduce costs, and accelerate delivery on mission-critical programs. We are backed by leading investors including Lux Capital, Founders Fund, and Andreessen Horowitz. Our fast-growing team is united by a shared mission to reindustrialize American manufacturing for the 21st century and beyond!

The Role

You will transform manufacturing operations through predictive analytics at Hadrian. As our Manufacturing Analytics Data Scientist, you'll build forecasting models that predict everything from cycle times to tool failures. Working with limited but high-quality data, you'll develop innovative approaches to predict queue dynamics, optimize inventory levels, and forecast demand in the complex world of aerospace manufacturing. Your models will directly impact on-time delivery, reduce waste, and enable proactive decision-making across our factories.

What You'll Do

• Develop cycle time prediction models accounting for part complexity and operator variability.

• Build queue forecasting systems to predict bottlenecks before they occur.

• Create tool life prediction models using sensor data and usage patterns.

• Design inventory forecasting models balancing holding costs with stockout risks.

• Implement demand forecasting for high-mix, low-volume aerospace parts.

• Develop anomaly detection for quality issues and equipment failures.

• Build hierarchical forecasting models for multi-level BOM structures.

• Create simulation models to validate forecasting approaches.

• Design experiments to improve model accuracy with limited data.

• Implement real-time monitoring dashboards with predictive alerts.

• Develop APIs for model deployment and integration.

• Create feedback loops to continuously improve predictions.

• Document methodologies and train operations teams.

• Collaborate with engineers to understand data generation processes.

• Present insights and recommendations to leadership.

What We're Looking For

• Strong foundation in time series analysis and forecasting.

• Experience with manufacturing or operations analytics.

• Proficiency in Python and statistical programming.

• Understanding of uncertainty quantification and prediction intervals.

• Experience working with limited, high-value data.

• Knowledge of survival analysis and reliability modeling.

• Ability to build models that work with sparse data.

• Strong visualization and communication skills.

• Experience with real-time analytics and streaming data.

• Understanding of causal inference and confounding.

• Ability to design meaningful experiments.

• Experience deploying models to production.

• Domain knowledge in manufacturing or supply chain.

• Collaborative mindset and business acumen.

Compensation

For this role, the target salary range is $160,000 - $240,000 (actual range may vary based on experience).

This is the lowest to highest salary we reasonably and in good faith believe we would pay for this role at the time of this posting. We may ultimately pay more or less than the posted range, and the range may be modified in the future. An employee's pay position within the salary range will be based on several factors, including, but not limited to, relevant education, qualifications, certifications, experience, skills, geographic location, performance, and business or organizational needs.

Benefits

• 100% coverage of medical, dental, vision, and life insurance plans for employees

• 401k

• Re