Data Scientist, Optimization - Real-Time Supply Management

<p>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.</p> <p>Data Science is at the heart of Lyft’s products and decision-making. Data Scientists at Lyft operate in dynamic environments, moving quickly to build the world’s best transportation solutions. We tackle a wide range of challenges - from shaping long-term business strategy with data, to making critical short-term decisions, to developing algorithms and models that power both internal systems and customer-facing products.</p> <p>Driver Incentives Science owns the algorithms and systems behind incentive design, influencing driver engagement and marketplace efficiency — from real-time supply positioning to longer-horizon earnings and engagement programs. The team is responsible for designing pay and incentive mechanisms that are efficient and good for driver experience over the long run.</p> <p>As a Data Scientist specializing in Algorithms, you'll partner closely with product, engineering, and operations leaders to build and scale incentive systems, shape long-term mechanism design strategy, and deliver on critical business goals tied to marketplace efficiency and driver earnings. Candidates with strong optimization backgrounds — think mathematical programming, control theory, or operations research — are a great fit, though we welcome strong candidates from machine learning or causal inference as well. The ideal candidate thrives in a fast-paced environment and brings a hands-on, entrepreneurial mindset to drive results.</p> <h2><strong>Responsibilities:</strong></h2> <ul> <li>Collaborate with engineering and product teams to design, implement, and iterate on new features and algorithmic improvements for driver incentives and pay mechanisms.</li> <li>Design, develop, and deploy optimization models, algorithms, and systems for problems such as budget allocation, multidimensional cost-curve development, and incentive targeting.</li> <li>Write production model code; collaborate with Software Engineers to implement algorithms in production.</li> <li>Perform exploratory data analysis to gain a deeper understanding of the marketplace and its users.</li> <li>Communicate findings and facilitate launch decisions with technical and non-technical stakeholders.</li> <li>Ensure robust experimentation and causal inference methodologies are applied to measure the impact of new features and strategies.</li> </ul> <h2><strong>Experience:</strong></h2> <ul> <li>Advanced degree (MS or PhD, PhD preferred) in a quantitative field like Operations Research, Applied Math, Computer Science, Statistics, Engineering, or a related area; or equivalent work experience.</li> <li>Passion for solving unstructured and non-standard mathematical problems, with 2+ years of hands-on experience in optimization (preferred), causal inference, or machine learning.</li> <li>End-to-end experience with data, including querying, aggregation, analysis, and visualization.</li> <li>Proficiency with Python.</li> <li>Strong ability to collaborate and communicate with others in a team setting.</li> <li>Experience seeking out and adopting new methods and techniques.</li> <li>Experience designing, running, and analyzing A/B tests to validate hypotheses and inform decision-making.</li> </ul> <h2><strong>Benefits:</strong></h2> <ul> <li>Extended health and dental coverage options, along with life insurance and disability benefits</li> <li>Mental health benefits</li> <li>Family building benefits</li> <li>Child care and pet benefits</li> <li>Access to a Lyf