Data Scientist, Algorithms

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 Scientist 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

• Design, develop, and deploy production-grade algorithms and machine learning models that power Lyft Business products such as Business Travel, Lyft Pass, and Concierge.
• Own the end-to-end lifecycle of modeling solutions—from problem definition, data exploration, feature engineering, and model development to validation, deployment, and post-launch monitoring.
• Translate ambiguous business problems into measurable, technical solutions, collaborating closely with Product, Engineering, and cross-functional stakeholders.
• Implement scalable model pipelines and contribute to high-quality, maintainable code used in production services.
• Conduct deep exploratory and causal analyses on large-scale datasets to identify opportunities for growth, operational efficiency, fraud detection, dispatch quality, pricing optimization, and user experience improvements.
• Run experiments and support causal inference frameworks, ensuring algorithm changes are rigorously measured and validated.
• Benchmark, tune, and optimize models for performance at scale—latency, throughput, reliability, and fairness.
• Contribute to technical documentation, model cards, reproducibility pipelines, and internal best practices.
• Stay current with emerging ML/AI research and proactively identify opportunities to introduce new techniques that enhance product capabilities.
• Collaborate in cross-functional planning, influencing direction through strong technical reasoning and data-driven insights.

Experience

• Master's degree or PhD in Machine Learning, Computer Science, Statistics, Applied Mathematics, Engineering, or a related quantitative field; or equivalent practical industry experience.
• 3 years of applied experience building, evaluating, and deploying ML models or algorithms in production systems.
• Strong proficiency in Python, applied ML frameworks (PyTorch, TensorFlow, JAX, scikit-learn), and familiarity with ML Ops concepts (feature stores, model deployment, monitoring).
• Experience working with large-scale datasets and distributed data processing tools and vendors (e.g., Spark, Snowflake, Databricks).
• Hands-on experience with algorithm development, supervised/unsupervised learning, time-series, optimization, or ranking/recommendation systems.
• Demonstrated ability to write clean, reliable, production-ready code and collaborate with Engineering on integrations, APIs, and model serving.
• Experience with A/B testing, experiment setup, or causal inference fundamentals.
• Ability to break down ambiguous problems, conduct rigorous analyses, and deliver actionable technical solutions.
• Strong communication skills, with the ability to explain complex modeling concepts to technical and non-technical stakeholders.
• A track record of impactful technical execution, intellectual curiosity, strong ownership, and a bias for action.

• Extended health and dental coverage options, along with life insurance and disability benefits
• Mental health benefits
• Family building benefits
• Child care and pet benefits
• Access to a Lyft funded Health Care Savings Account
• RRSP plan to help save for your future
• In addition to provincial observed holidays, salaried team members are covered under Lyft's flexible paid time off policy. The policy allows team members to take off as much time as they need (with manager approval). Hourly team members get 15 days paid time off, with an additional day for each year of service 
• Lyft is proud to support new parents with 18 weeks of paid time off, designed as a top-up plan to complement provincial programs. Biological, adoptive, and foster parents are all eligible.
• Subsidized commuter benefits

Lyft is committed to creating an inclusive workforce that fosters belonging. Lyft believes that every person has a right to equal employment opportunities without discrimination because of race, ancestry, place of origin, colour, ethnic origin, citizenship, creed, sex, sexual orientation, gender identity, gender expression, age, marital status, family status, disability, pardoned record of offences, or any other basis protected by applicable law or by Company policy. Lyft also strives for a healthy and safe workplace and strictly prohibits harassment of any kind.  Accommodation for persons with disabilities will be provided upon request in accordance with applicable law during the application and hiring process. Please contact your recruiter if you wish to make such a request.

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 at least 3 days per week, including 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 Toronto area is CAD $108,000 - CAD $135,000. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Range is not inclusive of potential equity offering, bonus or benefits. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.