At Lyft, our mission is to improve people’s lives with the world’s best transportation. To do this, we start with our own community by creating an open, inclusive, and diverse organization.

Data Science is at the heart of Lyft’s products and decision-making. You will work in a dynamic environment, where we embrace moving quickly to build the world’s best transportation by making Lyft safe and affordable. Data Scientists on this team take on a variety of problems, ranging from developing the next generation insights from ride data to building on those insights to shape products that impact Safety on the platform. You will partner with data scientists, engineers, product, design and operations stakeholders across the entire Lyft organization and drive roadmaps to power Lyft’s suite of safety and insurance products.

We are looking to hire an expert in Machine Learning, Signal Processing and/or Statistics to join the Telematics team. We're looking for execution-oriented scientists who are passionate about solving challenging problems with data and mathematical models, and are excited about working in a fast-paced, innovative environment and take on some of the most interesting and impactful problems in ridesharing.

You will report to a Data Science Manager in the Risk team.

Responsibilities: Partner with other scientists, engineers and product managers across the Telematics team to roadmap, develop and productionize new safety insights Perform exploratory data analysis to gain a deeper understanding of problems, assess feasibility of an idea and surface new use cases for our Telematics data Develop and fit statistical and machine learning models, as well as use signal processing techniques to develop insights Partner with teams across Risk and other teams at Lyft to ensure successful adoption of safety insights into products Effectively communicate findings and facilitate decisions along the model and product development cycles Develop dashboards and processes to monitor the health of our data and insights pipelines, and mitigate disruptions to downstream consumers Experience: M.S. or Ph.D. in Computer Science, Engineering, Statistics, or other quantitative fields 1-2+ years of professional experience for PhDs or 2-4+ years for Master’s in a data scientist role  Passion for solving unstructured and non-standard mathematical problems End-to-end experience with data, including querying, aggregation, analysis, and visualization Proficiency with Python in a production environment Familiar with SQL - able to write structured and efficient queries on large data sets Ability to collaborate and communicate with others to solve a problem Strong oral and written communication skills, and ability to collaborate with cross-functional partners Benefits: Extended health and dental coverage options, along with life insurance and disability benefits Mental health benefits Family building benefits Access to a Health Care Savings Account In addition to provincial observed holidays, team members get 15 days paid time off, with an additional day for each year of service  4 Floating Holidays each calendar year prorated based off of date of hire 10 paid sick days per year regardless of province 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible

Lyft proudly pursues and hires a diverse workforce. Lyft believes that every person has a right to equal employment opportunities without discrimination because of race, ancestry, place of origin, colour, ethnic origin, citizenship, creed, sex, sexual orientation, gender identity, gender expression, age, marital status, family status, disability, pardoned record of offences, or any other basis protected by applicable law or by Company policy. Lyft also strives for a healthy and safe workplace and strictly prohibits harassment of any kind.  Accommodation for persons with disabilities will be provided upon request in accordance with applicable law during the application and hiring process. Please contact your recruiter now if you wish to make such a request.

This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office 3 days per week on Mondays, Thursdays and a team-specific third day. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year.