Software Development

Lead Data Scientist

We deliver supply chain solutions for the freight industry that are built on top of IoT sensor data from trucks. We're backed by investors in Waterloo, Toronto, SF, and NYC and are looking to add to our team.

Our mission is to connect the right shipment with the right truck at the right time. At our core, we are removing friction for supply chain stakeholders through the use of data. Here are some of the questions we work on every day: What patterns can we observe and predict using historical geospatial data? How can we use design thinking to build simple, effective, and user-friendly products that can be used by drivers, dispatchers, shippers, and brokers? How do we identify supply and demand preferences that are constantly evolving? How do we ensure our applications are highly performant, secure, available, and scalable? How can we provide more value to our users by partnering and collaborating with other companies in the industry? What innovative solutions can we introduce in the industry that can fundamentally transform logistics?

We will contribute to a greener environment by removing wasteful miles driven by unloaded trucks and make significant systemic improvements to logistics in North America. If this goal excites you, and this challenge intrigues you, let's talk!

In this role you will:

  • Lead the technical efforts of our data science team
  • Work with the product and engineering teams to propose, prototype, and formalize new data science-based features and functionality in line with business objectives
  • Translate product requirements into data science projects and initiatives
  • Develop and validate machine learning, optimization, and other algorithms that enable critical product functionality
  • Document, communicate, and educate stakeholders on product capabilities powered by statistical analyses, machine learning, and operations research
  • Assess feasibility of proposed data-based initiatives
  • Set up and run experiments in AWS or other cloud environments
  • Document and present findings and recommendations to stakeholders
  • Maintain subject matter expertise by keeping up with the latest literature on machine learning and operations research

You’re right for the role if you have these skills


  • 5+ years experience applying machine learning in a non-academic environment–ideally in a high-growth software development environment
  • Degree in a technical discipline, such as Machine Learning, Data Science, Operations Research, Computer Science, Electrical Engineering, Physics, Statistics, Computational Biology, or other technical field
  • Facility for distilling technical results and processes for lay users and internal stakeholders
  • Expertise in linear algebra, probability, statistics, data structures, and algorithms
  • Passion for deriving and communicating insights from large data sets
  • Experience with common data science and machine learning toolkits, such as Numpy, Pandas, Scikit-learn
  • Expert understanding and/or experience with the ML stack in AWS
  • Familiarity with common visualization toolkits, such as Matplotlib and Kepler

Nice to have: 

  • Experience with supply chain, logistics, and/or freight
  • Experience productizing geospatial, time-series, telematics data
  • Experience deploying ML Ops pipelines
  • Graduate degree in a technical discipline, such as Machine Learning, Data Science, Operations Research, Computer Science, Electrical Engineering, Physics, Statistics, Computational Biology, or other technical field


  • Range $120,000-$200,000 USD/year


  • 4 Weeks PTO 
  • Medical insurance including dental and vision (US & Canada)
  • Stock options
  • 401k

Hiring Process

  • Résumé review
  • Time speaking with a member of the team about your previous experiences, culture fit, and working style (30-45 minutes)
  • Team interviews (45-60 minutes)
  • Executive interviews (45-60 minutes)
  • Take-home assignment / Assessment of work sample (Up to 48-hour window)
Apply for this job

Company Information

Offices and team size:

The team is currently 30 core people in a remote work environment.

Team and Culture

We are dedicated to maintaining a high quality of work which enables our employees to continually grow in the capacities that they desire. At the same time, we are automating the trucking industry and competing on a scientific and technical level with billion-dollar companies.

This is a balancing act in which we all participate, and this is why only the best and most altruistic people are with us. To connect and deliver innovative results, we must care for and understand others. FleetOps operates as a team that is collectively committed to these values and is willing to grow within the company.

Diversity & Inclusion

At FleetOps, we value diversity and are proud to have a distributed, international team. 

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.