Staff Data Scientist

Joby Aviation-posted 3 months ago

$151,900 - $202,500/Yr

Full-time • Senior

Santa Cruz, CA

1,001-5,000 employees

Transportation Equipment Manufacturing

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As a Staff Data Scientist on the Data Analytics core team, you will be a technical leader responsible for deriving critical insights that directly influence the safety, reliability, and performance of our aircraft. This role goes beyond analysis; you will architect and build scalable, production-grade data science solutions, translating complex data from flight tests, manufacturing, and operations into actionable intelligence. You will serve as a mentor and a key technical voice, working across highly technical disciplines to define data strategy and solve our most challenging problems. The ideal candidate is a proactive and seasoned expert who thrives on ambiguity, is passionate about building robust systems, and is excited to apply their skills to the future of transportation.

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, NumPy, 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 TensorFlow
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 development and Ops for GenAI LLMs and Machine Learning, with a past record of successful projects delivery end-to-end
Expert use of IDE's for authoring, refactoring and debugging code
Ability to navigate a quickly changing environment, independently tackle ambiguous problems, and deliver high-impact solutions with limited supervision
Experience leading projects from conception to completion
Proven ability to communicate complex technical concepts to diverse audiences, from junior engineers to executive leadership

Direct experience with anomaly/outlier detection in high-frequency time-series sensor data
Experience developing and deploying models in a production environment using modern MLOps principles and tools (e.g., MLflow, Kubeflow)
Experience with version control and CI/CD platforms, able to manage your software through its entire lifecycle (development, testing, deployment)
Familiarity with physics-based modeling, digital twins, or advanced signal processing techniques
Experience with cloud platforms (AWS, GCP, Azure) and Infrastructure as Code (IaC) tools like Terraform or Kubernetes
Experience in the aerospace, automotive, battery technology, or another hardware-intensive industry

Paid time off
Healthcare benefits
401(k) plan with a company match
Employee stock purchase plan (ESPP)
Short-term and long-term disability coverage
Life insurance

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