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BI
Beehive Industries
Senior Data Scientist
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What they do
A Data Scientist utilizes skills and experience to systematically answer questions using data to provide actionable recommendations. Commonly utilizes advanced statistical analysis and machine learning techniques. Common responsibilities also include data cleaning and data management.
$102,537 / year median in Colorado
+18% projected growth
Job Description
Senior Data Scientist Beehive Industries is dedicated to Powering American Defense by revolutionizing the design, development, and delivery of jet propulsion systems to support the warfighter. Through the integration of additive manufacturing, the company aims to meet the growing and urgent needs for unmanned aerial defense by dramatically improving a jet engine's speed to market, fuel efficiency, and cost. Founded in 2020, the company is headquartered in Centennial, Colorado, with additional facilities in Knoxville, Tennessee, Loveland Ohio, and Mount Vernon, Ohio. Beehive is committed to grow and advance the defense industrial base while manufacturing exclusively in the USA. This role will be located at our Centennial, Colorado facility.
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
- Support troubleshooting and resolution of data-related issues in production environments
- Collaborate with data owners and subject-matter experts to define authoritative datasets, shared metrics, business logic, and common data definitions.
- Partner with IT and cybersecurity teams to ensure data science solutions align with enterprise architecture, infrastructure, security, and support requirements.
- Evaluate emerging technologies and technical approaches that can improve Beehive's analytical and digital engineering capabilities.
- Enable improved visibility into production health, manufacturing performance, and engine test data.
- Develop analytical applications that are intuitive, actionable, and aligned with the needs of end users.
- Develop automated testing and validation frameworks for data transformations, models, analytical applications, and decision-support tools.
- Ensure solutions are designed with appropriate configuration control, documentation, auditability, and change management.
- Support adoption of data-driven decision-making by translating technical outputs into clear operational insights and recommendations.
Requirements:
- Bachelor's or master's degree in computer engineering, Computer Science, Software Engineering, Artificial Intelligence, 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.
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Preferred Qualifications:
- Background in aerospace engineering, flight systems, or manufacturing operations.
- Experience with digital thread ecosystems and integration into ERP/MES platforms, preferred experience.
- Experience with Palantir Foundry
- Government/DoD project engagement and compliance experience.
- Published research, patents, or thought leadership in ML/AI for aerospace If this sounds like you, please submit an application with your resume.