Senior Data Scientist, Algorithms, Lyft Biz

The role, as LYFT, Inc. describes it

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 Senior Data Scientist to lead technical initiatives across the entire Lyft Business product suite. In this role, you will shape the technical vision, define algorithmic roadmaps, and drive execution for data science projects that accelerate growth, improve operational efficiency, and deliver measurable value to our enterprise partners. You’ll collaborate closely with Product, Engineering, Design, and Go-to-Market teams to build production ML 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, and experimentation, alongside strong business acumen in B2B contexts and a proven track record of technical leadership in fast-paced, cross-functional environments.

Responsibilities

• Technical Leadership: Lead complex Machine Learning, AI, and causal inference initiatives across Lyft Business products (Business Travel, Lyft Pass, Concierge) in ambiguous, high-impact problem spaces.

• End-to-End Modelling: Own the complete lifecycle of algorithmic solutions—from problem formulation, data exploration, and feature engineering to deployment, monitoring, and iteration.

• Production Deployment: Partner closely with Engineering to build and scale production-grade ML systems, real-time inference services, batch pipelines, and feature stores.

• Experimentation & Rigor: Define offline/online metrics, evaluation frameworks, and A/B testing strategies to ensure algorithms are reliable, fair, and aligned with business outcomes.

• System Optimization: Continually improve model performance across latency, accuracy, cost, and reliability using advanced tuning and scientific rigor.

• Algorithmic Innovation: Drive scientific excellence by introducing modern techniques in ML, optimization, reinforcement learning, or graph-based methods to unlock new product capabilities.

• Cross-Functional Influence: Translate complex business challenges into concrete algorithmic solutions in close collaboration with Product, Engineering, Operations, and Science teams.

• Mentorship & Quality Bar: Mentor junior and mid-level scientists, providing technical guidance, conducting modeling critiques, and contributing to Lyft's broader ML standards and tooling.

Experience

• Master’s or PhD in Machine Learning, Computer Science, Statistics, Optimization, or a related quantitative field (or equivalent applied experience)

• Industry Background: 5+ years of hands-on experience developing, deploying, and maintaining production machine learning models and optimization systems.

• Core Technical Expertise: Deep knowledge of supervised/unsupervised learning, ranking/decisioning systems

Read the full advert and apply on LYFT, Inc.’s site →