Principal Data Scientist

About Otto Aerospace

Otto Aerospace is developing the world’s first fifth-generation business jet, designed for sustainability through the innovative use of advanced super-laminar aerodynamics and high-precision, net-shaped composites. Flight tests of our technology demonstrator validate a dramatic reduction in fuel burn and allow a sizeable improvement in cabin comfort. Otto Aerospace is designing world-class aircraft from first principles physics and delivering ground-breaking aircraft and economic performance.

Job Summary

Otto Aerospace is seeking a dynamic and technically proficient Full-Stack Data Scientist to join its AI Design and Innovation Lab. In this role, you will contribute to translating complex data into impactful insights and tools that drive mission-critical decisions across various business functions. You will play a critical role in advancing Otto's AI initiatives by building production-grade machine learning systems, optimizing model performance, and supporting innovation in next-generation technologies.

 What You'll Do

• Data Science and Analytics

• Lead data discovery efforts, framing business problems as data science problems and guiding the team toward data-informed strategies.
• Build, train, validate, and tune machine learning models using advance statistical and machine learning techniques and tools
• Build analytics tools that deliver insights across business functions and domains
• Cloud Architecture & DevOps
• Design, build, and maintain CI/CD pipelines to automate build, test, and deploy workflows.
• Architect solutions using Azure (preferred), AWS, or GCP cloud services for data ingestion, processing, modeling, and serving.
• Champion DevOps culture and promote continuous integration and delivery best practices.
• Strategic Leadership & Collaboration
• Translate business needs into actionable data science solutions, evaluating multiple approaches and clearly communicating trade-offs
• Represent the AI team in cross-functional conversations and roadmap planning.
• Provide mentorship and technical guidance to team members and end-users on analytics tools and best practices. 
• Innovation and Continuous Improvement: 
  • Stay current with emerging technologies and industry trends in data analytics, machine learning, and IoT. 
  • Propose and implement innovative approaches to enhance data-driven decision-making and operational efficiency. 

Who You Are

Education

• A Bachelor's degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) with a minimum of 8 years of experience
• A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) with a minimum of 4 years of experience

Experience

• 4 - 8 years of experience in a Full-Stack Data Science, MLOps, or AI Engineering role.

• Hands-on experience in designing, deploying, and maintaining production-grade machine learning systems.
• Proven ability to work with both structured and unstructured data in large-scale environments.

Required Skills

• Machine Learning and AI:
  • Experience with LLMs, NLP, generative AI, and advanced deep learning techniques.
  • Proficiency in scikit-learn, PyTorch, TensorFlow, and distributed training frameworks.
• Infrastructure and Pipelines:
  • Knowledge of scalable data pipelines, inference systems, and cloud computing platforms (e.g., AWS, Google Cloud, Azure).
  • Familiarity with vector databases, ETL pipelines, and real-time processing systems.
  • Hands-on experience with DevOps tools: Docker, Jenkins, Kubernetes, GitHub Actions, Terraform or similar.
• Programming and Development:
  • Proficiency in Python and C++ for building production-grade systems.
  • Experience with software development practices such as version control (Git), containerization (Docker), and API design.
• Data Processing and Analysis:
  • Expertise in feature engineering, ETL processes, and handling large-scale datasets.
  • Strong command of SQL and tools for data manipulation and analysis.

Preferred Skills

• Background in aviation and/or aerospace analytics.
• Familiarity with monitoring tools such as Prometheus, MLflow, and OpenTelemetry.
• Experience in deploying AI systems with Terraform, Kubernetes, or similar DevOps tools.
• Experience integrating AI with digital twin models or simulation environments.
• Knowledge of MLOps best practices (model versioning, A/B testing, drift monitoring).

Soft Skills

• Strong problem-solving and analytical thinking abilities.
• Excellent communication and collaboration skills to work with cross-functional teams.
• Ability to manage competing priorities and deliver high-quality work within deadlines.

Where You'll Be

**This role is remote with travel to company headquarters in Ft Worth, TX, 1 week every 4-6 weeks for team collaboration

Benefits

Otto Aerospace provides a robust benefits package that includes competitive salaries, subsidized medical, dental, and vision coverage, 401(k) opportunities, paid short term disability, voluntary long-term disability and additional term life, with 15 paid days off, 15 paid holidays, and paid sick leave. Depending on seniority and role, some roles qualify for potential bonuses and stock options.

Otto Aerospace is an Equal Opportunity Employer 

We are committed to diversity, equity, and inclusion in every aspect of our hiring process. All applicants will be considered for employment regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, or disability. We believe that a diverse team brings fresh perspectives, innovative ideas, and greater success. The more inclusive we are, the stronger we become. Applicants must be legally authorized to work in the U.S.

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