Data Scientist

Overview

Joby Overview:
Imagine a piloted air taxi that takes off vertically, then quietly carries you and your fellow passengers over the congested city streets below, enabling you to spend more time with the people and places that matter most. Since 2009, our team has worked steadily to make this dream a reality. We’ve designed and tested many generations of prototype aircraft capable of serving in a network of electric air taxis.

We’re looking for talented, committed individuals to join our team as we push onward toward certifying the Joby aircraft, scaling our manufacturing, and launching our initial commercial service.

• Collaborate with data scientists, other cross-functional teams and subject matter experts on software engineering projects
• Conduct data analysis and interpret sensor data from a number of physical processes (aircraft, simulators, reliability test equipment, subsystem tests, etc.)
• Understand both data systems and physical systems, analyzing high-frequency time-series data from flight tests, battery systems, acoustic sensors, and manufacturing processes to identify patterns, anomalies, and performance trends
• Leverage advanced statistical methods, signal processing, and machine learning to fuse disparate data sources and build comprehensive models of complex physical systems
• Architect, design, and lead the development of scalable, end-to-end data science and machine learning systems for production use
• Define the technical roadmap for data analysis and predictive modeling within key areas of the business, identifying new opportunities to leverage data for strategic advantage
• Establish and champion best practices for software engineering, MLOps, and data modeling within the data science team
• Mentor and guide junior and senior data scientists, elevating the technical capabilities of the entire team through code reviews, design discussions, and knowledge sharing
• Act as a key technical liaison between the data team and other engineering departments (e.g., Aerodynamics, Powertrain, Manufacturing), translating business needs into technical requirements
• Develop robust, maintainable, and well-tested Python libraries and tools to automate data processing and analysis pipelines
• Design and build insightful dashboards and visualizations to communicate findings clearly to both technical and non-technical stakeholders
• Present complex analytical results and strategic recommendations to engineering teams and executive leadership, driving data-informed decision-making
• Comfortable navigating a quickly changing environment and willing to learn on-the-fly to obtain and define requirements
• Stay current with advancements in software and data engineering

• S. or Ph.D. in Computer Science, Engineering, Statistics, or a related quantitative field, or equivalent experience
• 10+ years of professional, hands on coding experience in data science and machine learning or a related role, with a demonstrated track record of leading complex projects from ideation to production deployment
• Expert-level software-engineering: deep expertise in architecting and writing clean, scalable, and maintainable code. You are a thought leader in software design patterns and best practices
• Expert proficiency in Python and its core data science libraries (e.g., Pandas, Num Py, Scikit-learn)
• Advanced SQL and Data Modeling: 6+ years of experience writing complex, performant SQL queries and designing efficient data models and pipelines for analytical purposes
• Advanced proficiency with Spark: 4+ years distributed computing frameworks preferably in a cloud environment like Databricks
• Strong background in data science, data analysis and visualization (algorithms, data structures, and architectures), probability, statistics, and predictive modeling
• Strong background in Machine Learning using packages such as PyTorch, Keras or Tensor Flow
• Ability to troubleshoot complex issues across multiple levels of abstraction
• Proficiency with Unix-based platforms, shell scripting, and Git source control
• Experience with data pipeline architectures, ingestion, ETL, transformations, analytics, API connectors and visualization
• Strong experience with…