Data Scientist - Machine Learning

Zoba

United States Remote

Full time

Sep 6

Zoba builds leading spatial optimization products to improve the efficiency of cities and the lives of people that live in them. Zoba’s API-first platform powers operations and dynamic pricing for the world’s top urban mobility operators in over 250 cities around the globe. Zoba speeds adoption of electric, sustainable urban mobility solutions by increasing operational efficiency and profitability of operators. Zoba was founded out of Harvard and MIT and is backed by leading investors including CRV, Founder Collective, and Mark Cuban.

Zoba’s decision automation products are built on top of physically-motivated probabilistic models and mathematical optimization, and use relatively few traditional machine learning techniques. The primary responsibility of this role is to identify, design, implement, and maintain machine learning-based improvements to Zoba’s current and future products.

 

In this role you will:

  • Build and refine models of urban mobility and logistics networks
  • Design, implement, and maintain machine learning models which improve the efficiency of urban services
  • Utilize Zoba’s industry-leading micromobility dataset: more than 400 million events and growing rapidly
  • Be responsible for technical product development as Zoba expands into new verticals
  • Collaborate closely with Zoba’s engineering team to build technical products
  • Help customers understand Zoba’ technical methodologies

What we are looking for:

  • 2+ years work experience in data science
  • An interest in cities, logistics, or mobility
  • Prior experience writing and maintaining production code
  • Prior experience deploying machine learning at scale
  • Experience with statistics or mathematical optimization

This is a senior-level individual contributor position. The role will be based in Boston.

At Zoba, we view diversity as a strength and are committed to creating an inclusive environment for employees of all backgrounds. 

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Zoba

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