Staff Data Scientist

Xwing

Santa Cruz (CA)

On-site

USD 147,000 - 235,000

Full time

14 days+
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Job summary

Joby is seeking a Staff Data Scientist to lead production-grade data science solutions across flight tests, manufacturing, and operations. You will architect scalable ML systems, mentor teams, and partner with Aerodynamics, Powertrain, and Manufacturing to translate data into strategic decisions.

The role requires deep experience in Python, ML, Spark, SQL, and cloud data platforms, with strong communication skills for executive audiences. This is a high-impact, fast-changing environment.

Qualifications

  • MS/PhD in CS/Engineering/Statistics or related field.
  • 10+ years hands-on coding in data science and ML with leadership in production deployments.
  • Expert-level software engineering with scalable, maintainable codebase.
  • Proficiency in Python and core libraries (Pandas, NumPy, Scikit-learn).
  • Advanced SQL and data modeling for analytics workflows.
  • Spark and distributed computing; cloud experience (Databricks).
  • Strong data science, statistics, and predictive modeling background.
  • Experience with ML frameworks (PyTorch, Keras, TensorFlow).
  • Unix, shell scripting, and Git proficiency.
  • Experience with data pipelines, ETL, analytics, and CI/CD for GenAI/LLMs.
  • Ability to mentor, influence across teams, and communicate to diverse audiences.

Responsibilities

  • Collaborate with data scientists and engineers on software projects.
  • Analyze high-frequency time-series data from flight tests and manufacturing.
  • Build scalable end-to-end data science and ML systems for production use.
  • Lead and mentor data scientists; perform code reviews and design discussions.
  • Translate business needs into technical requirements and roadmaps.
  • Develop robust Python libraries and data processing pipelines.
  • Create dashboards and visualizations for technical and non-technical stakeholders.
  • Present analytical results and strategic recommendations to leadership.

Skills

Python
Machine Learning
SQL
Spark
Data Visualization
Unix
Git
Databricks

Education

MS/PhD in CS/Engineering/Statistics

Tools

Databricks
TensorFlow/Keras/PyTorch

Job description

Staff Data Scientist

Job Locations: US-CA-Santa Cruz

  • ID: 2026-5315
  • Category: Product
  • Type: Regular Full-Time
Company 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. At Joby, we've been working to make that dream a reality since 2009 and we're now in the final stages of certifying our aircraft with the FAA. With plans to launch our aircraft in the US and Dubai, we're now scaling manufacturing and preparing for the launch of our commercial service.

Overview

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.

Responsibilities
  • 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
Requirements
  • M.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 experience writing complex, performant SQL queries and designing efficient data models and pipelines for analytical purposes
  • Advanced proficiency in Spark and distributed computing frameworks, with experience in cloud environments 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
Desired
  • 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
Additional Information

Compensation at Joby is a combination of base pay and Restricted Stock Units (RSUs). The target base pay for this position is $147,200 - $234,500/yr. The compensation package will be determined by job-related knowledge, skills, and experience.

Joby also offers a comprehensive benefits package, including paid time off, healthcare benefits, a 401(k) plan with a company match, an employee stock purchase plan (ESPP), short-term and long-term disability coverage, life insurance, and more.

Joby is an Equal Opportunity Employer

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