--- title: 'Data Science Intern, Algorithms (Summer 2027) at Lyft' canonical: 'https://feeny.ai/job/data-science-intern-algorithms-summer-2027-lyft-toronto-0s0884ee3bqs' type: 'job' last_seen: '2026-09-15' --- # Data Science Intern, Algorithms (Summer 2027) at Lyft - **Company:** Lyft - **Location:** Toronto, Canada - **Posted:** 2026-09-11 - **Last confirmed live:** 2026-09-15 - **Apply:** https://app.careerpuck.com/job-board/lyft/job/8767697002?gh_jid=8767697002 ## Job description 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. Lyft’s Data Science Team builds mathematical models underpinning the platform’s core services. Compared to other technology companies of a similar size, the set of problems that we tackle is incredibly diverse. They cut across optimization, prediction, modeling, inference, transportation, and mapping. We're looking for Masters or PhD students who are passionate about solving mathematical problems with data and are excited about working in a fast-paced, innovative and collegial environment. We are hiring for a variety of Data Science interns, focusing on the following specialties: - Optimization: Construct and fit statistical or optimization models that facilitate automated decision making in the app. - Machine Learning: Design, build, tune, and deploy machine learning models with a special emphasis on feature engineering and deployment. - Inference: Design and analyze tests in our dynamic marketplace, estimating statistical and ML models to enable better decisions, and developing and evaluating algorithmic policies in our pricing, dispatch, and incentives systems. You will report into a Science Manager. Responsibilities: - Partner with Engineers, Product Managers, and other cross-functional partners to frame problems, both mathematically and within the business context - Perform exploratory data analysis to gain a deeper understanding of the problem - Write production modeling code; collaborate with software engineers to implement algorithms in production - Design and run both simulated and live traffic experiments - Analyze experimental and observational data; communicate findings including working with partner teams and presentations; facilitate launch decisions Experience: - Currently pursuing a Masters or PhD degree at a university in Canada (required) in mathematical sciences (Operations Research, Computer Science, Statistics, Applied Mathematics, Theoretical Physics, Behavioral Science, Electrical Engineering, etc.), Economics (Microeconomics Theory, Econometrics etc.), Data Engineering; or a related field; AND with a graduation date between December 2027 and June 2028 (required) - Available during Summer 2027 for an internship in Toronto - Experience coding in Python (required) or SQL, R; standard data science libraries (NumPy, Scikit-learn, PyTorch, TensorFlow, Keras); and ML Tools & Libraries (NumPy, SpaCy, NLTK, Scikit-learn, TensorFlow, Keras) - Experimental design and analysis - Exploratory data analysis - Expertise in one of these specialties: optimization and mathematical modeling, machine learning fundamentals, or probabilistic and statistical modeling - Bonus points: Experience in marketplace design, ridesharing, studying two-sided marketplaces, and/or transportation Benefits: - Mental health benefits - In addition to holidays, interns receive 2 days paid time off and 3 days sick time off - Subsidized commuter benefits and Lyft ride credits 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. The expected base pay range for this position in the Toronto area is CAD $45 - CAD $48 per hour. 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. Lyft may use artificial intelligence to screen applicants, however, Lyft employees make the ultimate selection and hiring decisions. This is a new position. ## About Lyft ## Company Overview - **One-liner**: Lyft operates a ride-hailing, bikeshare, and scooter platform that connects drivers and riders, aiming to reduce personal car ownership and make cities more livable. - **Entity Type**: Public (NASDAQ: LYFT) - **Headquarters**: San Francisco, California, USA - **Founded**: 2012 - **Founders**: Logan Green and John Zimmer ## Core Business - **Primary industry/industries**: Mobility, Transportation, Ride-hailing, Micromobility - **Target customers**: B2C (riders and drivers), B2B (Lyft Business for enterprise commutes), and public sector (transit partnerships) - **Mission or purpose statement**: "To serve and connect" — building a more connected world, ride by ride. ## Products & Services - **[Lyft Rideshare]**: The core on-demand ride-hailing service connecting passengers with drivers. Type: Platform / Service. - **[Lyft Pink]**: A subscription membership offering perks like discounted rides, priority airport pickups, and free bike/scooter unlocks. Type: Subscription. - **[Lyft Business]**: A suite of tools for companies to manage employee commutes, client rides, and delivery logistics. Type: B2B SaaS / Service. - **[Lyft Bikes & Scooters]**: Shared electric bikes and scooters available in select cities, including the Bixi network in Montreal. Type: Micromobility Service. - **[Lyft Flexdrive]**: A car rental program for drivers who don't own a vehicle, enabling them to earn on the platform. Type: Service / Fleet Management. - **[Lyft Ads]**: In-app advertising platform allowing brands to reach riders and drivers. Type: Ad Tech / Marketplace. ## Market Standing - **Valuation/Market Cap**: Approximately $4.5 billion (as of mid-2025, market cap fluctuates). **Not publicly available** for private valuation — public company. - **Key Metric**: Annual Revenue of approximately $4.4 billion (FY 2023), with $1.3 billion in Q1 2025 reported revenue. - **Notable Investors/Partners**: Major institutional investors include Fidelity, Vanguard, and BlackRock. Key partners include Uber (in some markets, e.g., transit data sharing), Motivate (bikeshare operator), and various municipal transit agencies. - **Growth Signals**: Launched Lyft Ads in 2024; expanded into autonomous vehicle partnerships (Waymo, Motional); opened new offices in Toronto (2024) and Mexico City (2022); strong recovery in ride volumes post-pandemic. ## Competitive Advantages - **Differentiated brand and culture**: Known for a friendlier, more community-oriented brand compared to competitors, with a focus on driver and rider safety. - **Integrated multimodal platform**: Combines ride-hailing, bikes, scooters, and public transit info in one app, making it a one-stop mobility solution. - **Strong transit partnerships**: Deep integrations with city transit agencies (e.g., Montreal's Bixi, LA Metro) provide a unique public-sector moat. - **Data & network effects**: Large dataset on urban mobility patterns enables better routing, pricing, and demand prediction. ## Strategic Focus - **Autonomous vehicle (AV) readiness**: Building partnerships and infrastructure to integrate AVs into the platform, positioning for a future without human drivers. - **Advertising revenue**: Scaling Lyft Ads to create a new high-margin revenue stream, leveraging its large user base. - **International expansion**: Selectively entering new markets (e.g., Canada, Mexico) and deepening presence in existing ones via bikeshare and transit. - **Profitability**: Continued focus on operational efficiency and cost discipline to achieve sustained GAAP profitability. ## Why Work Here - **Culture**: Lyft emphasizes a welcoming, inclusive culture with core values like "Be yourself," "Make it happen," and "Uplift others." The company fosters a strong sense of belonging through Employee Resource Groups (ERGs) and community events. - **Remote/Hybrid/Office Policy**: Hybrid model — employees are expected in the office a few days a week, with flexibility. Offices are designed with tech-equipped workspaces, stocked kitchens, and themed rooms. - **Notable Perks**: - **Health & Well-being**: Comprehensive medical, dental, vision; free One Medical membership; free access to therapists via Modern Health. - **Time Off**: Unlimited paid vacation for salaried US employees; generous PTO for hourly employees. - **Parental Leave**: 18 weeks of paid leave for all new parents (biological, adoptive, foster). - **Financial**: 401(k) plan with financial training sessions. - **Commute**: Free Lyft Pink membership; pre-tax commuter benefits. - **Learning**: Udemy subscription for professional development; mentorship programs for interns and new grads. - **Office Environment**: Dog-friendly offices; regular team offsites and social events. - **Engineering Culture**: Known for high-impact work on large-scale distributed systems, machine learning, and mobile engineering. Early-career talent is highly valued, with structured mentorship and real project ownership. ## Sources 1. [Lyft Careers](https://www.lyft.com/careers) 2. [Lyft Life at Lyft](https://www.lyft.com/careers/life-at-lyft) 3. [Lyft Early Talent Programs](https://www.lyft.com/careers/early-talent) 4. [Lyft Homepage](https://www.lyft.com/) 5. 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