Data Scientist, In-car Ads

Data Scientist, In-car Ads

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.

Lyft connects people to transportation to change the way we live and get around our communities. As a member of the Science team, you will work in a dynamic environment, where we embrace moving quickly to build the world's best transportation. Data Scientists take on a variety of problems ranging from shaping critical business decisions to building algorithms that power our internal and external products. We're looking for passionate, driven Data Scientists to take on some of the most interesting and impactful problems across the business from our New York City office. As a Data Scientist for Lyft Media – you will work on one of Lyft's newest lines of business focused on building the world's largest transportation media network. We build products that allow brands to engage with our unique audience throughout their transportation journeys. This role will be focused on our In-car Ads product / business line.

Responsibilities:

• Define key metrics & build dashboards to monitor business and product performance
• Leverage data to build analytic frameworks to identify opportunities for growth and efficiency
• Build data pipelines & maintain high quality of data collection / processing
• Partner with product managers, engineers, and operators to translate analytical insights into decisions and action
• Design and analyze experiments; communicate results and act on launch decisions
• Understand Lyft's strategic and competitive position. Help set your team's goals, success metrics and roadmap to align with Lyft Media's mission and drive maximum impact based on data analysis, market research and usability studies.

Experience:

• Degree in a quantitative field such as statistics, economics, applied math, operations research or engineering (advanced degrees preferred), or relevant work experience
• 2+ years of experience in data science or analytics at a high-growth technology company.
• Experience working on two-sided marketplaces. Experience with adtech products or hardware preferred but not required
• Strong proficiency in SQL - able to write structured and efficient queries on large data sets & build visualizations of them
• Experience in programming, especially with data science and visualization libraries in Python or R
• Experience with data engineering & quality assurance
• Strong oral and written communication skills, and ability to collaborate with and influence cross-functional partners to make business decisions
• Experience leading post-launch optimizations including developing experimentation strategies

Benefits:

• Great medical, dental, and vision insurance options
• Mental health benefits
• Family building benefits
• In addition to 12 observed holidays, salaried team members have unlimited paid time off, hourly team members have 15 days paid time off
• 401(k) plan to help save for your future
• 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
• Pre-tax commuter benefits
• Lyft Pink - Lyft team members get an exclusive opportunity to test new benefits of our Ridership Program

Lyft is an equal opportunity/affirmative action employer committed to an inclusive and diverse workplace. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law.

The expected range of pay for this position in the US is $139,500-$155,000. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Range is not inclusive of potential equity offering, bonus or benefits. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.