Data Scientist, Algorithms - Pricing - Rider Engagement

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.

Data Science is at the heart of Lyft’s products and decision-making. Data Scientists at Lyft operate in a dynamic environment, and partner closely with cross-functional teammates to tackle a variety of highly open-ended business problems to build the world’s best transportation solutions.

The Pricing team is a centerpiece of Lyft’s marketplace, determining prices for all rideshare products and supporting new initiatives, and Rider Engagement is an integral part of that. Rider Engagement manages one of the most impactful marketplace and business levers, driving both short term and long term business outcomes. The team owns the algorithms and systems behind incentive offers, budget management, operational control and real-time optimization.

We are looking for fast learning, data-driven individuals who are passionate about tackling these open-ended problems in pricing theory and making a large, positive impact in the business. In this role, you will work closely with Product, Engineering and Analytics on a cross-functional team to develop and iterate incentive levers, prototype and build end-to-end solutions that can operate at scale. In addition, you will be expected to leverage your domain knowledge and influence existing and future roadmaps to help Lyft continue to deliver a better experience for riders and drivers.

Responsibilities:

• Partner with other Scientists, Engineers, Product Managers, and Business Partners to frame problems mathematically and within the business context

• Write production code. Collaborate with Software Engineers to implement algorithms in live systems and ensure the robustness of the systems

• Develop and fit statistical, machine learning, or optimization models. Deploy production-grade models that solve business problems.

• Design, implement, and analyse different types of experiments, and facilitate data-driven and informed decision making and prioritization

• Establish metrics and development measurement methodologies to monitor the health of our products, as well as the impacts on user and marketplace outcomes

• Perform deep dive analysis to gain a deeper understanding of the problem and uncover new product and business opportunities

• Drive collaboration and coordination with cross-functional teams. Communicate findings to a broad audience consisting of Product, Engineering, and executive leadership.

Experience:

• M.S. or Ph.D. in Machine Learning, Operations Research, Statistics, Computer Science or other quantitative fields

• 1-4+ years professional experience for PhDs or 3-5+ years for Master’s in a Data Science role in a technology company setting

• Proven experience with building and evaluating optimization or machine learning models

• Proficiency with Python and working in a production coding environment

• Passion for solving unstructured and non-standard mathematical problems

• End-to-end experience with data, including querying, aggregation, analysis, and visualization

• Strong verbal and written communication skills, and ability to collaborate and communicate with others to solve a problem

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 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

• Lyft Pink - Lyft team members get an exclusive opportunity to test new benefits of our Ridership Program

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, geneti