Senior Data Scientist
A hands-on senior data scientist who designs, builds, and maintains data pipelines, data models, and production-grade analytics/ML solutions in Palantir Foundry for aerospace engineering and manufacturing operations. Core stack is Python, SQL, and ML/MLOps, with strong emphasis on traceability, security, and configuration control.
- Compensation
- $120K–$150K / yr
- Location
- Centennial, CO
- Work setup
- Not specified
- Seniority
- Senior
- Employment
- Not specified
- Experience
- 5+ years
- Category
- Data science
- Posted
Skills
Must have
- Bachelor's or master's degree in computer engineering, computer science, software engineering, AI, or related technical discipline
- 5+ years of experience leading software engineering, AI/ML, digital engineering, or industrial technology organizations
- Demonstrated ability to design, code, test, deploy, and support production-grade data science solutions
- Experience building scalable data pipelines and working with complex, high-volume, or heterogeneous data
- Strong understanding of data architecture, data modeling, data governance, metadata, lineage, and data quality practices
- Strong technical background in distributed systems, software architecture, cloud platforms, data engineering, and AI/ML systems
- Strong proficiency in Python and SQL
- Strong understanding of modern AI/ML frameworks, MLOps practices, and enterprise software delivery methodologies
- Deep knowledge of machine learning, experimental design, uncertainty analysis, model evaluation, and data visualization
- Experience operating in highly regulated environments requiring cybersecurity, traceability, and configuration control
- Excellent executive communication, organizational influence, and strategic planning skills
- Ability to obtain and maintain a U.S. government security clearance
- U.S. citizenship required
Nice to have
- Background in aerospace engineering, flight systems, or manufacturing operations
- Experience with digital thread ecosystems and integration into ERP/MES platforms
- Experience with Palantir Foundry
- Government/DoD project engagement and compliance experience
- Published research, patents, or thought leadership in ML/AI for aerospace
Full description
Role Overview:
The Senior Data Scientist will serve as a hands-on technical leader responsible for designing, building, and maintaining data pipelines and infrastructure that support critical business intelligence and operational analytics for our aerospace engineering and manufacturing operations.
This individual will partner closely with the Information Technology, Engineering, and Manufacturing leaders to develop reliable data architecture, analytical applications, and production-grade data science solutions within Beehive’s digital infrastructure, including Palantir Foundry.
The central focus of this role will be ensuring that tools built using company data are reliable, robust, secure, traceable, maintainable, and extensible. The Senior Data Scientist will establish technical standards and reusable patterns while personally performing the detailed work required to build data pipelines, analyze complex datasets, develop models, validate results, and deploy solutions into operational use.
The ideal candidate combines deep expertise in data science, statistics, software engineering, and data architecture with experience applying those disciplines in aerospace, defense, or advanced manufacturing. This individual must be equally comfortable solving difficult technical problems independently, leading complex cross-functional initiatives, and mentoring other team members.
Responsibilities:
· Design and develop scalable data pipelines and ETL processes to ingest, transform, and load data from diverse aerospace manufacturing systems and enterprise applications
· Build and optimize data models in Palantir Foundry to support analytics, reporting, and machine learning use cases using Python, SQL, statistical methods, machine learning, LLMs, optimization, and analytical software engineering practices.
· Collaborate with data analysts, scientists, and business stakeholders to understand data requirements and implement solutions that drive actionable insights
· Build and deploy models and analytical tools supporting applications such as print anomaly detection, quality forecasting, financial insight, process optimization, production scheduling, and engine performance analysis.
· Move concepts beyond prototypes by engineering them for production reliability, maintainability, scalability, security, and operational adoption.
· Optimize database performance and manage data infrastructure to support high-volume, real-time data processing
· Document data architectures, pipelines, and processes to ensure knowledge transfer and operational continuity
· Participate in code reviews, contribute to engineering best practices, and mentor junior team members