Data Science Manager, Lyft Business

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 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.

Lyft Business builds products that help organizations move the people who matter most—employees, customers, patients, and guests—easily and efficiently. Our offerings include Business Travel, Lyft Pass, and Concierge (for healthcare and non-healthcare rides), enabling companies to manage transportation at scale through APIs, integrations (e.g., Concur, Expensify), and dedicated tools. These platforms power high-impact B2B use cases across corporate travel, healthcare access, customer experience, and community programs.

We are seeking a Data Science Manager to lead initiatives across the entire Lyft Business product suite. In this role, you will shape the vision, define the roadmap, and drive execution for data science projects that accelerate growth, improve operational efficiency, and deliver measurable value to our partners. You’ll collaborate closely with Product, Engineering, Design and Go-to-Market teams to build models, experimentation frameworks, and advanced analytics that inform strategy and power product innovation.

This is a high-visibility, high-impact role with direct influence on Lyft’s enterprise offerings. The ideal candidate will bring deep expertise in algorithm development, machine learning, causal inference, experimentation; strong business acumen in B2B contexts; and a proven track record of leading teams in fast-paced, cross-functional environments.

Responsibilities: 

• Lead, mentor, and grow a high-performing team of data scientists focused on algorithm development, machine learning, experimentation and advanced analytics for Lyft Business.
• Define and execute the data science vision and roadmap for innovation across the Lyft Business product suite, ensuring alignment with overall business strategy.
• Design, develop, and deploy algorithms and models that power core product capabilities.
• Partner with Product, Engineering, and Design to integrate solutions into scalable, production-grade systems and customer-facing experiences.
• Establish robust experimentation and causal inference frameworks to measure the business impact of algorithmic changes.
• Conduct deep analyses of complex, large-scale datasets to uncover opportunities for growth, operational efficiency, and improved user experience.
• Champion data-driven decision-making, ensuring that product and strategy decisions are informed by rigorous quantitative analysis.
• Drive innovation by staying current with emerging research, technologies, and industry best practices in algorithms, optimization, and applied machine learning.

Experience: 

• PhD (preferred) or Master’s degree in a quantitative field such as Machine Learning, Computer Science, Statistics, Engineering, or a related discipline; or equivalent practical experience.
• 8+ years of progressive experience in data science, machine learning, optimization, or causal inference, including building and deploying algorithms in production systems
• 3+ years of people management experience leading high-performing technical teams, with a proven ability to mentor, develop, and retain top talent.
• Demonstrated ability to set a strategic vision for data science and translate it into impactful, scalable solutions that drive measurable business outcomes.
• Deep expertise in machine learning, experimental design, causal inference, and statistical methodologies, with a track record of applying them to high-stakes product or marketplace decisions.
• Experience navigating complex, ambiguous problem spaces and guiding teams through prioritization, tradeoffs, and execution.
• Strong communication and influence skills, with the ability to engage both technical and executive stakeholders, align priorities, and build consensus.
• Hands-on proficiency with large-scale data processing tools  and machine learning frameworks (e.g., PyTorch, TensorFlow, scikit-learn).

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