Head of Weather Systems

Zipline•South San Francisco, CA

12h•Onsite

About The Position

Zipline is the world’s largest and most experienced drone delivery service, on a mission to serve all humans equally by ensuring access to food, medicine and essential goods anytime, anywhere. They design, build, and operate the world’s largest autonomous logistics system, delivering critical supplies quickly and reliably. Today, Zipline operates on four continents, makes a delivery somewhere in the world every 30 seconds, and has completed millions of deliveries to date, including blood, vaccines, medical supplies, food, and retail products. Their system strengthens supply chains, reduces congestion, and gives people time back, with more than 140 million commercial autonomous miles safely flown. Zipline is redefining access to healthcare, consumer products, and food across the globe. The company seeks practical problem solvers who thrive on real-world challenges and rapid growth, motivated by building systems that have a direct, meaningful impact on people’s lives and by scaling the future of logistics. The Head of Weather Systems will be at the center of informing Zipline on the critical environmental conditions that their aircraft must fly in to achieve business goals, whilst owning the automated system that enforces those limits operationally to ensure flight safety and protecting an excellent and informed customer experience.

Requirements

Minimum of 5+ years of industry experience
Proven people leader or clearly ready to own and develop a small team (3-5 direct reports)
Advanced proficiency with scientific python and libraries commonly used for data analysis, e.g., Pandas, Numpy, Scipy, and Matplotlib, XArray, NETCDF
Ability to learn new languages and libraries for use in daily work (eg. Rust, C++)
Familiarity with geospatial and meteorological datasets, formats, and tools
Understand how to efficiently process large datasets across distributed systems
Strong understanding of descriptive statistics, probability and linear algebra
Mastered a wide range of machine learning and statistical techniques, and developed an intuition for what tool to apply in every situation
Adept at summarizing large datasets visually that make complex results understandable at a glance to different audiences
Ability to find creative ways to take the uncertainty of weather prediction and turn it into certainty for the business
Excellent understanding of meteorology and climatology, and an ability to communicate the underlying physics and their challenges to a broad audience
Highly self-directed; able to drive a roadmap and ruthlessly prioritize, balancing a core roadmap against the emerging needs of a fast-scaling and complex system
Proven in setting the pace of a small team, striving to continuously improve the development tools and processes and help folks around you work smarter
Willingness to learn aircraft flight and aviation weather and regulation rapidly

Nice To Haves

Cloud-native experience with Kubernetes and/or AWS
Experience with kafka or other streaming data systems
Experience with aircraft flight and aviation weather and regulation
An ability to manipulate the weather

Responsibilities

Design and develop our automated weather monitoring systems to make real-time go/no-go decisions for missions, as well as forecast in-coming weather conditions that would require pausing deliveries
Define the requirements on flyable weather conditions to achieve business performance goals that are achievable in the context of automated risk system performance
Set the pace on simulation- and real-world-based weather-related validation strategies, including performance of the weather system risk decisions, operations simulations to determine the role of the weather system on customer experience dynamics, and developing representative but tractable weather models in Zipline’s high fidelity flight simulation tools
Enable and maintain strong and unambiguous communication with customer, fulfilment and flight operations teams, setting expectations for the system uptime, on both seasonal and daily timescales
Drive the development of ground- and air-based sensing to support the risk posture calculations in a scalable and cost-effective way