As a Data Scientist, Decisions in the Rider team, you will leverage data and apply analytical thinking and inference to shape our rider and partner product vision and make business decisions that put our customers first. You will identify improvement opportunities, propose and implement technical solutions, design experiments, and measure the impact of your team's decisions. You will partner closely with product, engineering, design, research, marketing and business development to deliver products end-to-end. You will also collaborate and build alignment with adjacent teams outside of Rider to balance driver, rider and marketplace needs. We're looking for well-rounded, passionate, driven Data Scientists to take on some of the most interesting and impactful problems in ridesharing.
Responsibilities:- Drive roadmap across Rider Segments, Loyalty and Partnerships teams. Be a primary participant in defining team goals and setting the priorities of projects for the team to address.
- Partner with org leads in product, engineering, UX research, design and marketing to initiate, design, develop and scale zero-to-one products and drive business strategy through data-centric presentations
- Define and maintain key objectives to align with the overarching goals of Rider, Marketplace and Lyft.
- Apply modeling, advanced analytics, experimentation and causal inference techniques to drive decision-making at Lyft.
- Drive cross-org impact and alignment, shaping product and business strategy through data-centric presentations
- Advise teams on best practices. Be a thought leader and go-to expert for stakeholders and dependency teams
- Provide technical guidance and mentorship to junior team members on solution design, implementation, as well as lead code reviews.
Experience:- M.S. and at least 6 or Ph.D. and at least 4 years of relevant work experience
- Degree in economics, applied math, statistics, engineering or other quantitative fields; strong preference for M.S.+
- Proficiency in SQL - able to write structured and efficient queries on large data sets
- Fluency in programming, especially with data science and visualization libraries in Python or R
- Technical leadership experience with a team of decisions and algorithms data scientists, interfacing VP or C-level executives.
- Experience designing and analyzing complex A/B experiments, and communicating results and recommendations to cross-functional stakeholders
- Strong oral and written communication skills (i.e, business writing, presentation building & delivery, executive briefings)
- Ability to build relationships and collaborate with senior cross-functional stakeholders to drive shared outcomes
- Experience working with ETL pipelines a plus
Benefits:- 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
- 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
- Subsidized commuter benefits
- Monthly Lyft credits and complimentary Lyft Pink membership
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, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid
The expected base pay range for this position in the New York City area is $176,000 - $220,000, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.
