Senior Data Scientist - Machine Learning (Remote)

United States

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Lime

Go car-free with the world’s largest shared electric vehicle company. Lime is on a mission to build a future where transportation is shared, affordable…

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Lime is the world's largest shared electric vehicle company. We are on a mission to build a future of transportation that is shared, affordable and carbon-free. Named a Time 100 Most Influential Company in 2021, Lime has powered more than 350 million electric bike and scooter rides in more than 200 cities across five continents, saving an estimated 75+ million car trips. Learn more at li.me!

Data is at the core of every decision at Lime - from designing vehicles, to deploying them, enhancing the user’s experience, optimizing our supply chain or warehouse operations. Every team at Lime engages with Data Science & Analytics. Our goal is to provide data insights and models that drive better business outcomes.  
We are looking for intellectually curious, highly motivated individuals to join our Data Science & Analytics team. You will partner with our Engineering, Product, and Operations teams to identify critical issues to the business, develop a deep understanding of them, and design scalable solutions. You will leverage your quantitative and modeling skills to transform signals into insights, and insights into actions. You should have strong ML or optimization modeling skills, analytical insights, excellent communication abilities, and a knack for working across teams in a fast-paced environment. 
This position is a US based remote position. The individual hired into this role must be comfortable supporting multiple time zones across the globe with primary support to Pacific Time. 

What You'll Do:

  • Build models using Python that help optimize business decisions. Examples include demand forecasting, routing and labor pricing. 
  • Develop a deep understanding of a particular problem space that’s relevant to the business and propose solutions to improve it
  • Guide product and strategic decisions with experimentation and in-depth analyses

About You:

  • MS or PhD in Economics, Statistics, Applied Mathematics, or other quantitative fields
  • 4+ years of industry experience as a Data Scientist
  • Hands-on Machine Learning model development experience using Python is required
  • Hands-on experience with SQL
  • Hands-on experience with data pipelines and visualization tools
  • Deep and practical understanding of probability and statistics, including causal inference
  • Solid understanding of Machine Learning algorithms - practical experience building ML models preferred
  • Solid understanding of optimization algorithms - practical experience around vehicle routing problem preferred

What we offer:

  • Opportunity to revolutionize transportation in cities around the world with the leader in urban mobility solutions
  • Scale with a rapidly growing organization, with significant opportunity for growth
  • Play a role in the transformation of urban mobility and sustainability
  • Work with a team of successful, fun and motivated people
  • Competitive salary and benefits
In accordance with Colorado State Law, if the candidate selected for this job resides in Colorado, the anticipated minimum salary will be $132,000.00, plus bonus and equity (when eligible), as well as benefits. Exact salary will ultimately depend on the candidate’s qualifications. In addition to base salary, this role will be eligible for a variable bonus based on a combination of management discretion and employee performance.
#LI-Remote#LI-AM1
Lime is an Equal Opportunity Employer, but that’s only the start. We strive to build a workforce composed of individuals with different backgrounds, abilities, identities, and mindsets—not just to do great work, but to become a better company and grow as individuals.

Tags: Causal inference Data pipelines Economics Engineering Machine Learning Mathematics ML models PhD Pipelines Python SQL Statistics

Perks/benefits: Career development Competitive pay Equity Salary bonus Startup environment

Regions: Remote/Anywhere North America
Country: United States
Job stats:  44  11  0

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