Data Scientist - Machine Learning, Pricing & Rider Engagement
At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.
What this role actually needs.
Data Scientist - Machine Learning, Pricing & Rider Engagement at Lyft in New York City. UpJobz keeps this listing high-signal for applicants targeting serious high-tech roles across the United States, Canada, and Mexico. At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.
Day-to-day expectations
A clear list of the work this role is designed to cover.
- Partner with Engineers, Product Managers, and Business Partners to frame problems mathematically and within the business context
- Prioritize and lead deep dives into our data to uncover new product and business opportunities
- Be familiar with production code; collaborate with Software Engineers to implement algorithms and models in production
- Design, implement, and analyse different types of experiments, and facilitate and foster data-driven and informed decision making and prioritization
- Establish metrics that measure the health of our products, as well as rider and driver experience
- Drive collaboration and coordination with cross-functional teams
What a strong candidate brings
This keeps the job page specific, readable, and easier to match.
Why people would want this job
Benefits help searchers understand whether the role is a real fit before they apply.
- Great medical, dental, and vision insurance options with additional programs available when enrolled
- Mental health benefits
- Family building benefits
- Child care and pet benefits
- 401(k) plan with company match to help save for your future
- In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off
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Next moves
- Tailor your resume around machine-learning and research instead of sending a generic application.
- Use the first two bullets of your application to connect your background directly to data scientist - machine learning, pricing & rider engagement is a high-signal on-site role in new york city, and it is most realistic for united states residents.
- Open the role quickly if it fits and bookmark three similar jobs before you leave the page.
Interview themes
Watchouts
- Compensation is hidden, so get range clarity in the first recruiter conversation.
- Use united states residents as part of your positioning so the recruiter does not have to infer it.
- Show concrete examples of succeeding in on-site environments.
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