Data Science Expert
2 days ago
At Lyft, our mission is centered around enhancing people's lives by delivering the world's best transportation. To achieve this, we focus on creating an inclusive and diverse organization where everyone feels valued.
Data science plays a crucial role in Lyft's products and decision-making processes. As a member of the Rider team, you will work in a dynamic environment that fosters collaboration and rapid innovation. Data Scientists tackle various problems ranging from critical business decisions to developing algorithms for internal and external products. We seek passionate and driven Data Scientists to address some of the most intriguing and impactful challenges in ridesharing.
In the Rider team, as a Data Scientist - Decision Making, you will leverage data and rigorous analytical thinking to shape our rider app and inform business decisions that prioritize customer satisfaction. You will identify opportunities, set priorities, recommend technical solutions, design experiments, and measure their impact. This requires a quantitative mindset when making decisions in partnership with product, design, engineering, business, and operations stakeholders throughout the organization.
You will report to a Data Science Manager in the Rider Science team.
Key Responsibilities:
- Utilize data and analytical frameworks to uncover growth and efficiency opportunities
- Collaborate with product managers, engineers, marketers, designers, and operators to translate data insights into actionable decisions and strategies
- Design and analyze online experiments; effectively communicate results and drive launch decisions
- Develop analytical frameworks to monitor business and product performance
- Establish metrics to gauge the health of our products, as well as rider and driver experiences
Required Skills and Qualifications:
- A degree in a quantitative field such as statistics, economics, applied mathematics, operations research, or engineering (advanced degrees are preferred)
- 3+ years of industry experience in a data science or analytics role
- Proficiency in SQL - capable of writing structured and efficient queries on large datasets
- Experience in programming, particularly with data science and visualization libraries in Python or R is advantageous
- Experience in online experimentation and statistical analysis
- Strong oral and written communication skills, with the ability to collaborate and influence cross-functional partners
Benefits:
- Comprehensive health and dental coverage options, including 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 enjoy 15 days paid time off, with an additional day for each year of service
- 4 Floating Holidays each calendar year prorated based on 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 strives for a diverse workforce and believes that every person deserves equal employment opportunities without discrimination due to race, ancestry, place of origin, color, ethnic origin, citizenship, creed, sex, sexual orientation, gender identity, gender expression, age, marital status, family status, disability, pardoned record of offenses, or any other basis protected by applicable law or Company policy. Additionally, Lyft prioritizes a healthy and safe workplace and strictly prohibits harassment of any kind. Accommodations for individuals with disabilities will be provided upon request during the application and hiring process.
This role will involve working 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. Furthermore, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year.
The estimated salary for this position ranges from $140,000 to $170,000 per year, depending on location and experience. This figure is based on national averages and may vary accordingly.
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