Zipline

San Francisco

501-1,000 employees

Zipline operates the world's largest autonomous on-demand delivery system with the industry's leading instant logistics technology stack.

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Data Scientist

Zipline

Data Scientist

Data Science

This job is no longer open

About Zipline

Do you want to change the world? Zipline is on a mission to transform the way goods move. Our aim is to solve the world’s most urgent and complex access challenges by building, manufacturing and operating the first instant delivery and logistics system that serves all humans equally, wherever they are. From powering Rwanda’s national blood delivery network and Ghana’s COVID-19 vaccine distribution, to providing on-demand home delivery for Walmart, to enabling healthcare providers to bring care directly to U.S. homes, we are transforming the way things move for businesses, governments and consumers. The technology is complex but the idea is simple: a teleportation service that delivers what you need, when you need it. Through our technology that includes robotics and autonomy, we are decarbonizing delivery, decreasing road congestion, and reducing fossil fuel consumption and air pollution, while providing equitable access to billions of people and building a more resilient global supply chain.

Join Zipline and help us to make good on our promise to build an equitable and more resilient global supply chain for billions of people.

About You and The Role

We are looking for a highly skilled data scientist to join our growing Data team. As a key member of the Data team, you will be primarily responsible for designing algorithms that improve operational efficiency. In this role, you’ll work cross-functionally with members of our Operations, Engineering, and Data teams to identify opportunities, brainstorm solutions, and implement production-quality algorithms. The ideal candidate is excited about solving ML, optimization, and causal inference problems and partnering with our Engineering teams to deploy your solutions in our software. You'll tackle exciting challenges like designing algorithms to optimize aircraft allocation at our various distribution centers and improve on-time delivery rates for incoming orders. Secondary responsibilities include analyzing data produced by our hardware devices and contributing to our internal data science libraries to help teams across the company. Your work will enable the entire organization to make more informed decisions, innovate faster, and serve our customers better.

What You'll Do

Partner with engineers, product managers, and business partners to identify algorithmic problems, come up with possible approaches, and recommend the best path forward.
Develop algorithms iteratively, building in the right level of complexity to solve the business problem at hand and support future improvements.
Define success criteria for your models so that you can measure impact and changes over time. You’ll be expected to communicate findings and drive continuous improvements.
Collaborate with Software Engineers to implement algorithms in production that scale gracefully.
Collaborate with stakeholders to prioritize projects and define requirements.
Carry out analysis on data produced by our hardware systems and create insightful visualizations to share your findings.
Contribute to internal libraries to help other teams with their data science needs including visualization, prediction, optimization, and inference.

What You'll Bring

Advanced proficiency with Python and libraries commonly used for data analysis, e.g., Pandas, NumPy, SciPy, and Matplotlib.
Strong understanding of machine learning algorithms, data modeling, and statistical analysis.
Knowledge of optimization and predictive modeling techniques and experience applying them to real-world problems.
Skilled at translating a general question or problem into a clearly defined algorithmic solution.
Ability to communicate clearly with both technical and non-technical audiences.
Ability to work independently and manage multiple projects simultaneously.
Nice to haves:

Experience with Databricks or PySpark
Experience with productionizing data models

What Else You Need to Know

Location: This is a remote friendly role, but you do have the option to come into our South San Francisco office if you’re based in the Bay Area. If you are full-time remote, you must be able to travel to our headquarters in South San Francisco to work with stakeholders periodically (1-2 times per quarter, at most).

Zipline is an equal opportunity employer and prohibits discrimination and harassment of any type without regard to race, color, ancestry, national origin, religion or religious creed, mental or physical disability, medical condition, genetic information, sex (including pregnancy, childbirth, and related medical conditions), sexual orientation, gender identity, gender expression, age, marital status, military or veteran status, citizenship, or other characteristics protected by state, federal or local law or our other policies.

We value diversity at Zipline and welcome applications from those who are traditionally underrepresented in tech. If you like the sound of this position but are not sure if you are the perfect fit, please apply!

Please Note

We have received reports stating that certain individuals are reaching out to people under false pretenses, claiming to be Zipline employees, affiliates, agents, or representatives. They may seek to gain access to your personal information or to acquire money from you by offering fictitious employment opportunities or by claiming that they are contacting you on Zipline’s behalf.

Genuine Zipline employees or representatives will never ask you for money or payment in exchange for employment opportunities or other related services. Any such offer of employment or any other service in exchange for fees that claims to be from us is deceitful and part of a fraud.

If you believe you have been targeted by a fraudulent party, we ask that you immediately get in touch with us via email at security@flyzipline.com upon receiving a suspicious offer or claim.

This job is no longer open