How you will contribute to revolutionizing electric aviation:
- Maintain and develop data pipelines that extract, transform, and validate data from data lakes and other sources
- Perform exploratory data analysis (EDA) to uncover trends and patterns
- Build data exploration tools and dashboards for technical stakeholders
- Develop, deploy and monitor machine learning models in production environments
- Design and implement data quality checks and monitoring systems
- Collaborate with cross-functional teams to address business problems with data-driven solutions
- Effectively communicate with both technical and non-technical stakeholders, translating complex data concepts into understandable insights and recommendations
- Work collaboratively with the Data Science team on technical design and architectural decisions while engaging directly with users to understand needs and iterate on solutions
- Take ownership of code and algorithms, ensuring thorough documentation and knowledge sharing to eliminate single points of ownership
- Conduct code reviews to maintain code quality, share knowledge, and uphold data science standards across the team
- Identify opportunities to eliminate manual workflows through automation and improved tooling
- Write clean, well-tested, production-ready code with comprehensive documentation following engineering best practices
Minimum Qualifications:
- Master's degree in a related field (Data Science, Mathematics, Computer Science) or equivalent practical experience
- 5+ years of professional Data Science experience building and maintaining production-grade machine learning models, data pipelines, dashboards, and analytical tools
- Proficiency in a statistical programming language (e.g., Python) with demonstrated ability to write clean, maintainable code
- Experience with data manipulation libraries (e.g., Pandas, NumPy)
- Proficiency in SQL and other database systems for data extraction and aggregation
- Experience with machine learning frameworks (e.g., Scikit-Learn, TensorFlow, PyTorch)
- Knowledge of ETL/ELT processes, data pipeline design, and data modeling best practices
- Experience with version control systems (Git), automated testing, and CI/CD practices
- Experience with cloud platforms (e.g., AWS, GCP, or Azure) and their data services
- Excellent problem-solving and analytical skills
- Excellent written and verbal communication skills, with ability to present findings to non-technical stakeholders and collaborate effectively across cross-functional teams
- A strong desire to learn and adapt in a fast-paced, dynamic environment
Above and Beyond Qualifications:
- Experience in aviation, aerospace, engineering, or manufacturing, with contextual domain knowledge related to the components of BETA Technologies
- Experience with data pipeline orchestration tools (e.g., Airflow)
- Experience with dashboard and visualization tools (e.g., Grafana, Tableau, PowerBI)
- Experience with DBT Core to build, test, and maintain data models
- Familiarity with large-scale data processing tools (e.g., Spark, Hadoop)
- Experience with knowledge graphs and graph databases (e.g., Neo4j, Amazon Neptune)
- Familiarity with containerization technologies (Docker)
- Experience deploying and using monitoring and alerting tools (e.g., Cloudwatch, Grafana)
Top Skills
What We Do
BETA Technologies is creating an electric transportation ecosystem that’s safe, reliable and sustainable. A relentlessly focused team is building an extensive charging infrastructure and ALIA, the world’s most technologically advanced electric vertical aircraft (EVA).
BETA’s platform and products are strikingly simple. Prioritization of safety and a pragmatic approach to certification drive elegant redundancy, appropriate diversity of implementation and simplicity of control. ALIA’s fixed-pitch propellers and centrally located batteries make it an inherently stable aircraft that is safe to fly and easy to maneuver.







