Data Scientist – Decisions (Pay, Identity & Integrity)


Information Scientist – Selections (Pay, Id & Integrity)

At Lyft, our mission is to enhance folks’s lives with the world’s finest transportation. To do that, we begin with our personal neighborhood by creating an open, inclusive, and various group.

As a Information Scientist within the Pay, Integrity & Id org, you’ll collaborate with our world class crew of engineers, product managers, analysts and different knowledge scientists to assist create finest at school pay platforms, cease fraudulent actors from harming our riders & drivers fraud and construct person belief on the Lyft platform. You’ll run experiments (A/B assessments) and develop knowledge pushed options to launch new options and take away the unhealthy actors from the Lyft platform whereas sustaining a optimistic expertise for real customers. We’re on the lookout for an intellectually curious particular person who has extraordinary consideration to element, a monitor document of analytical problem-solving and expert communication.


  • Design and analyze experiments in collaboration with different scientists, product & engineering; talk findings to stakeholders and facilitate launch choices
  • Leverage superior statistical methods to generate quantitative insights and develop machine studying fashions
  • Analyze the big variety of indicators obtainable to determine patterns in giant datasets and uncover root causes
  • Accomplice with product managers, engineers, and operators to translate analytical insights into choices and motion
  • Construct knowledge pipelines and develop analytical frameworks to watch enterprise and product efficiency
  • Set enterprise metrics that measure the well being of our merchandise, in addition to passenger and driver expertise
  • Collaborate with product and engineering and talk findings to stakeholders in a transparent and concise method


  • Diploma in a quantitative subject equivalent to statistics, economics, utilized math, operations analysis or engineering (superior levels most popular), or related work expertise
  • Prior expertise within the fintech, fraud or id house is most popular
  • 4-6+ years of trade expertise in a knowledge science or analytical position. 
  • Proficiency in SQL – in a position to write structured and environment friendly queries on giant knowledge units
  • Expertise in programming, particularly with knowledge science and visualization libraries in Python or R
  • Sturdy oral and written communication abilities, and skill to collaborate with and affect cross-functional companions 


  • Prolonged well being and dental protection choices, together with life insurance coverage and incapacity advantages
  • Psychological well being advantages
  • Household constructing advantages
  • Entry to a Well being Care Financial savings Account
  • Along with provincial noticed holidays, crew members get 15 days paid day off, with an extra day for annually of service 
  • 4 Floating Holidays every calendar 12 months prorated primarily based off of date of rent
  • 10 paid sick days per 12 months no matter province
  • 18 weeks of paid parental depart. Organic, adoptive, and foster dad and mom are all eligible

Lyft proudly pursues and hires a various workforce. Lyft believes that each individual has a proper to equal employment alternatives with out discrimination due to race, ancestry, native land, color, ethnic origin, citizenship, creed, intercourse, sexual orientation, gender id, gender expression, age, marital standing, household standing, incapacity, pardoned document of offences, or every other foundation protected by relevant regulation or by Firm coverage.  Lyft additionally strives for a wholesome and protected office and strictly prohibits harassment of any sort.  Lodging for individuals with disabilities can be supplied upon request in accordance with relevant regulation in the course of the utility and hiring course of.  Please contact your recruiter now if you happen to want to make such a request.

This position can be in-office on a hybrid schedule following the institution of a Lyft workplace in Toronto — Staff Members can be anticipated to work within the workplace 3 days per week on Mondays, Thursdays and a team-specific third day. Moreover, hybrid roles have the pliability to work from anyplace for as much as 4 weeks per 12 months.

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