Lyft

<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>As a Data Scientist in the Pay, Integrity &amp; Identity org, you will collaborate with our world class team of engineers, product managers, analysts and other data scientists to help create best in class pay platforms, stop fraudulent actors from harming our riders &amp; drivers fraud and build user trust on the Lyft platform. You will run experiments (A/B tests) and develop data driven solutions to launch new features and remove the bad actors from the Lyft platform while maintaining a positive experience for genuine users. We’re looking for an intellectually curious individual who has extraordinary attention to detail, a track record of analytical problem-solving and skilled communication.</p>
<p>Prior experience in the fintech, fraud or identity space is preferred.</p>
<h2><strong>Responsibilities: </strong></h2>
<ul>
<li>Design and analyze experiments in collaboration with other scientists, product &amp; engineering; communicate findings to stakeholders and facilitate launch decisions</li>
<li>Leverage advanced statistical techniques to generate quantitative insights and develop machine learning models</li>
<li>Analyze the wide variety of signals available to identify patterns in large datasets and uncover root causes</li>
<li>Partner with product managers, engineers, and operators to translate analytical insights into decisions and action</li>
<li>Build data pipelines and develop analytical frameworks to monitor business and product performance</li>
<li>Set business metrics that measure the health of our products, as well as passenger and driver experience</li>
<li>Collaborate with product and engineering and communicate findings to stakeholders in a clear and concise manner</li>
</ul>
<h2><strong>Experience: </strong></h2>
<ul>
<li>Degree in a quantitative field such as statistics, economics, applied math, operations research or engineering (advanced degrees preferred), or relevant work experience</li>
<li>4-6+ years of industry experience in a data science or analytical role. </li>
<li>Proficiency in SQL - able to write structured and efficient queries on large data sets</li>
<li>Experience in programming, especially with data science and visualization libraries in Python or R</li>
<li>Strong oral and written communication skills, and ability to collaborate with and influence cross-functional partners</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>Pet benefits</li>
<li>Access to a Lyft funded Health Care Savings Account</li>
<li>RRSP plan with company match to help save for your future</li>
<li>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 </li>
<li>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.</li>
<li>Subsidized commuter benefits and Lyft ride credits</li>
</ul>
<p>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.</p>
<p>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</p>
<p>The expected base pay range for this position in the Toronto area is CAD $108,000 - CAD $135,000, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.</p>
<p>Lyft may use artificial intelligence to screen applicants, however, Lyft employees make the ultimate selection and hiring decisions.</p>
<p>This job fills an existing vacancy.</p>

Data Scientist, Decisions - Payments

<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>The Safety and Customer Care (SCC) team at Lyft manages over 1.7 million monthly human and AI interactions and serves as Lyft's primary direct touchpoint with riders and drivers. We handle critical infrastructure that powers both human associates and AI agents to make riders and drivers feel safe and comfortable while riding or driving with Lyft, transforming every support interaction into a moment of genuine connection. </p>
<p>As a Data Scientist working on Causal Inference in SCC, you'll partner with a strong team of engineers, product managers, designers, and operations leaders to deliver a personalized and exceptional experience for Lyft customers, using rigorous causal inference to guide the highest-stakes decisions we make.</p>
<p>We're looking for a motivated and talented Data Scientist with deep causal inference expertise to join the SCC Data Science team. You'll partner closely with the area's tech lead on high-impact work spanning AI-powered support products, differentiated service, and operations optimization.</p>
<p>The ideal candidate brings sharp applied inference intuition, a bias toward impact, and the ability to cut through ambiguity in complex problem spaces. You'll work on projects like:</p>
<ul>
<li>Design rigorous experiments and quasi-experiments to measure the causal impact of SCC product and AI-agent launches, and drive data-informed launch decisions.</li>
<li>Build causal ML models to optimize concession budget allocation, targeting the right support credit, to the right rider or driver, at the right moment to maximize trust and business impact.</li>
<li>Quantify the long-term effects of support-experience changes on rider and driver retention, and uncover heterogeneous treatment effects across our community.</li>
<li>Deliver strategic insights on quality–cost tradeoffs, empowering leadership to balance service quality, coverage, and operational cost as we scale AI-powered support.</li>
</ul>
<h2>Responsibilities:</h2>
<ul>
<li>Inference &amp; Measurement: Design and implement causal inference frameworks and statistical models to measure the impact of interventions, evaluate system performance, and surface opportunities for improvement.</li>
<li>Modeling: Build, evaluate, and iterate on causal ML models that power high-stakes decisions, applying best practices across the full model lifecycle, from feature engineering to production deployment.</li>
<li>Optimization: Develop frameworks to analyze tradeoffs between competing objectives (accuracy, coverage, user experience, and operational cost), and propose strategies to improve overall effectiveness.</li>
<li>Collaborate Cross-Functionally: Build strong relationships with partners across Product, Design, Engineering, Operations, and Analytics to drive collaboration and innovation.</li>
<li>Influence Decisions: Communicate learnings to leaders and stakeholders in a clear, compelling way that drives informed, data-driven decision-making.</li>
<li>Empowerment: Think strategically about how to scale and evolve data science capabilities within SCC, contributing to the long-term vision for how science drives platform outcomes.</li>
</ul>
<h2>Experience:</h2>
<ul>
<li>2+ years of industry experience in causal inference or data science with a Master's degree in a quantitative field (statistics, economics, computer science, etc.), or a PhD in a relevant field.</li>
<li>Strong knowledge of causal inference and experimental design.</li>
<li>Experience with uplift modeling / heterogeneous treatment effect (CATE) estimation.</li>
<li>Proven ability to apply statistics to unstructured problems and deliver measurable results.</li>
<li>Expertise in SQL and experience with large-scale data platforms.</li>
<li>Proficiency in Python and working within production coding environments.</li>
<li>Proven ability to communicate clearly and effectively to audiences of varying technical levels.</li>
<li>Excellent project management, communication, and collaboration skills.</li>
<li>Experience partnering with operational teams and support systems (customer care workflows, agent operations, or credit budget allocation)</li>
<li>Experience working with AI/LLM applications (LLM-powered agents, retrieval systems, or evaluation frameworks) is nice to have.</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 Lyft funded Health Care Savings Account</li>
<li>RRSP plan with company match to help save for your future</li>
<li>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 </li>
<li>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.</li>
<li>Subsidized commuter benefits and Lyft ride credits</li>
</ul>
<p>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.</p>
<p>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</p>
<p>The expected base pay range for this position in the Toronto area is CAD $108,000 - CAD $135,000, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.</p>
<p>Lyft may use artificial intelligence to screen applicants, however, Lyft employees make the ultimate selection and hiring decisions.</p>
<p>This job fills an existing vacancy.</p>
<p> </p>

Data Scientist - Inference, Safety and Customer Care

<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>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.</p>
<p>We are seeking a <strong>Senior Data Scientist</strong> 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.</p>
<p>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.</p>
<h3>Responsibilities</h3>
<ul>
<li>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.</li>
<li>End-to-End Modelling: Own the complete lifecycle of algorithmic solutions—from problem formulation, data exploration, and feature engineering to deployment, monitoring, and iteration.</li>
<li>Production Deployment: Partner closely with Engineering to build and scale production-grade ML systems, real-time inference services, batch pipelines, and feature stores.</li>
<li>Experimentation &amp; Rigor: Define offline/online metrics, evaluation frameworks, and A/B testing strategies to ensure algorithms are reliable, fair, and aligned with business outcomes.</li>
<li>System Optimization: Continually improve model performance across latency, accuracy, cost, and reliability using advanced tuning and scientific rigor.</li>
<li>Algorithmic Innovation: Drive scientific excellence by introducing modern techniques in ML, optimization, reinforcement learning, or graph-based methods to unlock new product capabilities.</li>
<li>Cross-Functional Influence: Translate complex business challenges into concrete algorithmic solutions in close collaboration with Product, Engineering, Operations, and Science teams.</li>
<li>Mentorship &amp; Quality Bar: Mentor junior and mid-level scientists, providing technical guidance, conducting modeling critiques, and contributing to Lyft's broader ML standards and tooling.</li>
</ul>
<h3>Experience</h3>
<ul>
<li> Master’s or PhD in Machine Learning, Computer Science, Statistics, Optimization, or a related quantitative field (or equivalent applied experience)</li>
<li>Industry Background: 5+ years of hands-on experience developing, deploying, and maintaining production machine learning models and optimization systems.</li>
<li>Core Technical Expertise: Deep knowledge of supervised/unsupervised learning, ranking/decisioning systems, probabilistic modeling, and causal inference.</li>
<li>Technical Stack: Strong proficiency in Python, modern ML frameworks (PyTorch, TensorFlow, scikit-learn), and distributed data systems (Spark, Snowflake, Databricks).</li>
<li>Production ML Systems: Hands-on experience building end-to-end ML architectures, including online/batch pipelines, feature engineering, and automated monitoring frameworks.</li>
<li>Experimental Design: Demonstrated track record of designing rigorous experimentation strategies, A/B tests, and offline/online validation methodologies.</li>
<li>Domain Ownership: Proven ability to independently drive multi-project algorithmic scopes and navigate technical ambiguity from ideation to delivery.Communication &amp; Leadership: Exceptional ability to translate complex technical concepts for non-technical stakeholders, alongside a history of mentoring peers and raising technical bars.</li>
</ul>
<h2><strong>Benefits:</strong><strong><br /></strong></h2>
<ul>
<li>Great medical, dental, and vision insurance options with additional programs available when enrolled</li>
<li>Mental health benefits</li>
<li>Family building benefits</li>
<li>Child care and pet benefits</li>
<li>401(k) plan with company match to help save for your future</li>
<li>In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off</li>
<li>18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible</li>
<li>Subsidized commuter benefits</li>
<li>Monthly Lyft credits and complimentary Lyft Pink membership</li>
</ul>
<p>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, genetic information, or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law.</p>
<p>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 3 days per week 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</p>
<p>The expected base pay range for this position in the Seattle area is $136,160 - $170,200, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.</p>

Senior Data Scientist, Marketplace

<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>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.</p>
<p>We are seeking a <strong>Senior Data Scientist</strong> 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.</p>
<p>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.</p>
<h3>Responsibilities</h3>
<ul>
<li>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.</li>
<li>End-to-End Modelling: Own the complete lifecycle of algorithmic solutions—from problem formulation, data exploration, and feature engineering to deployment, monitoring, and iteration.</li>
<li>Production Deployment: Partner closely with Engineering to build and scale production-grade ML systems, real-time inference services, batch pipelines, and feature stores.</li>
<li>Experimentation &amp; Rigor: Define offline/online metrics, evaluation frameworks, and A/B testing strategies to ensure algorithms are reliable, fair, and aligned with business outcomes.</li>
<li>System Optimization: Continually improve model performance across latency, accuracy, cost, and reliability using advanced tuning and scientific rigor.</li>
<li>Algorithmic Innovation: Drive scientific excellence by introducing modern techniques in ML, optimization, reinforcement learning, or graph-based methods to unlock new product capabilities.</li>
<li>Cross-Functional Influence: Translate complex business challenges into concrete algorithmic solutions in close collaboration with Product, Engineering, Operations, and Science teams.</li>
<li>Mentorship &amp; Quality Bar: Mentor junior and mid-level scientists, providing technical guidance, conducting modeling critiques, and contributing to Lyft's broader ML standards and tooling.</li>
</ul>
<h3>Experience</h3>
<ul>
<li> Master’s or PhD in Machine Learning, Computer Science, Statistics, Optimization, or a related quantitative field (or equivalent applied experience)</li>
<li>Industry Background: 5+ years of hands-on experience developing, deploying, and maintaining production machine learning models and optimization systems.</li>
<li>Core Technical Expertise: Deep knowledge of supervised/unsupervised learning, ranking/decisioning systems, probabilistic modeling, and causal inference.</li>
<li>Technical Stack: Strong proficiency in Python, modern ML frameworks (PyTorch, TensorFlow, scikit-learn), and distributed data systems (Spark, Snowflake, Databricks).</li>
<li>Production ML Systems: Hands-on experience building end-to-end ML architectures, including online/batch pipelines, feature engineering, and automated monitoring frameworks.</li>
<li>Experimental Design: Demonstrated track record of designing rigorous experimentation strategies, A/B tests, and offline/online validation methodologies.</li>
<li>Domain Ownership: Proven ability to independently drive multi-project algorithmic scopes and navigate technical ambiguity from ideation to delivery.Communication &amp; Leadership: Exceptional ability to translate complex technical concepts for non-technical stakeholders, alongside a history of mentoring peers and raising technical bars.</li>
</ul>
<h2><strong>Benefits:</strong><strong><br /></strong></h2>
<ul>
<li>Great medical, dental, and vision insurance options with additional programs available when enrolled</li>
<li>Mental health benefits</li>
<li>Family building benefits</li>
<li>Child care and pet benefits</li>
<li>401(k) plan with company match to help save for your future</li>
<li>In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off</li>
<li>18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible</li>
<li>Subsidized commuter benefits</li>
<li>Monthly Lyft credits and complimentary Lyft Pink membership</li>
</ul>
<p>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, genetic information, or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law.</p>
<p>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 3 days per week 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</p>
<p>The expected base pay range for this position in the New York area is $136,160 - $170,200, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.</p>

<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>Machine Learning is at the heart of Lyft’s products and decision-making. Machine Learning Engineers at Lyft operate in dynamic environments, moving quickly to build the world’s best transportation solutions. We tackle a wide range of challenges, from pricing and marketplace frameworks that ensure reliability and competitiveness, to agentic AI platforms that automate analytical workflows, to behavioral detection systems that protect the integrity of our network. We operate at the intersection of applied ML and real business impact, shipping models that directly influence revenue, rider experience, and partner trust.</p>
<p>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.</p>
<p>We're looking for a Machine Learning Engineer to design, build, and deploy ML systems across Lyft Business. This is a high-scope role: you won't be siloed into one problem area. Instead, you'll move across pricing algorithms, fraud and behavior detection, agentic AI systems, and emerging ML applications as the business evolves. You'll write production-quality code, own models end-to-end from prototyping through deployment, and collaborate closely with Data Scientists, Product Managers, and Software Engineers to translate complex business problems into scalable ML solutions.</p>
<p>This role is ideal for someone who is technically versatile, energized by variety, and wants to see their work directly shape a large-scale business.</p>
<h2><strong>Responsibilities:</strong></h2>
<ul>
<li>Develop and deploy ML models across multiple problem domains — including dynamic pricing, marketplace optimization, fraud detection, and anomaly/behavior detection — in production environments serving millions of rides</li>
<li>Build and iterate on agentic AI systems (e.g., LLM-powered analytical agents) that automate decision-making and reduce operational overhead</li>
<li>Design and implement feature pipelines, model training workflows, and serving infrastructure using Lyft's ML platform</li>
<li>Partner with Data Scientists on the Algorithms and Decisions teams to take research prototypes from proof-of-concept to production at scale</li>
<li>Evaluate ML system performance against business KPIs, run experiments, and drive continuous model improvement</li>
<li>Identify new opportunities where ML can create leverage across Lyft Business verticals (Healthcare, Lyft Pass, Business Travel) and pitch solutions</li>
<li>Contribute to team engineering standards — code quality, observability, documentation, and testing practices</li>
</ul>
<h2><strong>Experience:</strong></h2>
<ul>
<li>Experience with GenAI / LLM ecosystems — prompt engineering, RAG, agent frameworks (e.g., LangChain, LangGraph), or fine-tuning</li>
<li>Exposure to graph-based ML methods (graph neural networks, knowledge graphs, network analysis)</li>
<li>Experience with pricing, marketplace, or fraud-related ML problems</li>
<li>Familiarity with cloud ML services (AWS SageMaker, Bedrock) or internal ML platforms</li>
<li>Track record of identifying and scoping ML projects independently, not just executing on pre-defined specs</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 Lyft funded Health Care Savings Account</li>
<li>RRSP plan with company match to help save for your future</li>
<li>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 </li>
<li>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.</li>
<li>Subsidized commuter benefits and Lyft ride credits</li>
</ul>
<p>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.</p>
<p>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</p>
<p>The expected base pay range for this position in the Toronto area is CAD $118,800 - CAD $148,500, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.</p>
<p>Lyft may use artificial intelligence to screen applicants, however, Lyft employees make the ultimate selection and hiring decisions.</p>
<p>This job fills an existing vacancy.</p>

Lyft

Open jobs at Lyft

Data Scientist, Decisions - Payments

Data Scientist - Inference, Safety and Customer Care

Senior Data Scientist, Marketplace

Senior Data Scientist, Marketplace

Machine Learning Engineer

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