At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.
Our transport network serves the needs of millions of people every day who want to get from one place to another using Lyft cars, bikes and scooters, with public transportation, or on foot in the most efficient way. To serve these needs, we need to suggest the fastest, most affordable and safest routes. We achieve this by processing millions of rides, taking into account the latest traffic information and analyzing the preferences of drivers.
To strengthen our efforts, we are hiring a Data Science Manager who will lead data scientists and data analysts helping us to make data driven decisions. Data Science & Analytics is at the heart of Lyft’s products and decision-making. You will leverage data and rigorous, analytical thinking to shape our mapping products and make business decisions that put our customers first. This will involve identifying and scoping opportunities, shaping priorities, recommending technical solutions, designing experiments, measuring the impact of new features and monitoring our solutions in close collaboration with many engineering teams. You will help us solve some of the most impactful problems in mapping, including:
- How do we provide the best routes and most accurate ETAs?
- How is the routing experience for our drivers? Are we providing the fastest, most economic and most comfortable routes to our customers?
- How do we benchmark and measure the success of map services?
Our technology stack is based on the latest technologies such as AWS, Kubernetes and Apache Airflow. You will work with incredibly passionate and talented colleagues from software engineering, machine learning and data science on projects that directly impact millions of riders and drivers.
Responsibilities
- Lead and grow a high-performing team of data scientists with diverse backgrounds, including optimization, experimentation, machine learning and causal inference
- Define and drive the data science vision, strategy, and roadmap, aligning with overall business and product objectives to improve market competitiveness and user experience
- Provide strong technical guidance and coaching to the team on complex data science problems related to real-time decision-making and resource allocation
- Champion data-driven decision-making and prioritization by partnering with product managers, engineers, marketers, and leaders to translate data insights into decisions and action
- Lead deep-dive analyses into large-scale datasets to identify opportunities for improving navigation efficiency, mapping accuracy, and overall product health
- Ensure robust experimentation and causal inference methodologies are applied to measure the impact of new features and strategies
- Mentor and guide the professional and technical development of your team members. Help develop their careers, and assign them to projects tailored to their skill levels, personalities, work styles, and professional goals
- Maintain a balance between building sustainable, high-impact projects and shipping things quickly
- Work closely with the Lyft recruiting team to hire high potential candidates from diverse backgrounds
Experiences
- Advanced degree (MS or PhD, PhD preferred) in a quantitative field like Operations Research, Computer Science, Statistics, Engineering, or a related area; or equivalent work experience
- 5+ years of hands-on technical experience in experimentation, causal inference, or data science, preferably with applications in real-time systems or marketplace dynamics
- 2+ years of management experience building, leading, and mentoring data science teams
- Strong expertise in statistics, experimental design, and causal inference, including A/B testing, multivariate testing, and incremental lift measurement
- Strong data storytelling and influence skills, with experience presenting insights and recommendations to senior leaders
- Experience launching and monitoring consumer facing products and iterating through data-driven experimentation and metrics analysis
- Experience guiding teams through ambiguous and complex technical challenges to deliver impactful solutions
- Hands-on experience building or operationalizing machine learning models (e.g., propensity, segmentation, churn, personalization) in partnership with engineering or platform teams (nice to have)
- Excellent communication and collaboration skills, with the ability to articulate complex technical concepts to diverse audiences
- Hands-on experience with large-scale data processing (e.g., Spark, SQL) and machine learning frameworks is highly desirable
- Prior experience in mapping domain will be 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
Lyft is an equal opportunity employer committed to an inclusive workplace that fosters belonging. 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, age, genetic information, or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law.
Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. 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 San Francisco 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.