Scientist in Toronto

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. As a Data Scientist on the Mapping team, you will collaborate with our world class team of scientists, engineers, product managers, and designers to grow and improve the quality of recommended routes and accuracy of our travel time estimations. We're looking for a passionate, driven Data Scientist who is excited to dive into our geospatial, behavioural and mobility data, and build a best-in-class mapping product that provides safe, efficient, and seamless navigation for our rideshare drivers. Data Science is at the heart of Lyft’s products and decision-making. You will leverage data and rigorous, analytical thinking to shape our mapping products and make business decisions that put our customers first. The Mapping team serves models and systems that determine the most efficient routes, fastest travel estimates and process real-time map data signals to detect traffic, closures and slowdowns. Working with our business and analytics partners, the team owns tools to ensure Lyft offers routes that our users trust. This will involve identifying and scoping opportunities, recommending technical solutions, designing experiments, and measuring the impact of new features. You will help us solve some of the most impactful problems in Mapping, including: How do we accurately predict acute and chronic traffic conditions? How do we improve the recommendations of our routing algorithms? How do we keep our travel estimation promises to our riders and drivers? How do we benchmark and measure the success of our services? Responsibilities: Own the complete lifecycle of algorithmic solutions from problem formulation, data exploration, and feature engineering to deployment, monitoring, and iteration Prioritize and lead deep dives into our data to uncover new product and business opportunities Partner closely with E

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. Driver Incentives Science owns the algorithms and systems behind incentive design, influencing driver engagement and marketplace efficiency — from real-time supply positioning to longer-horizon earnings and engagement programs. The team is responsible for designing pay and incentive mechanisms that are efficient and good for driver experience over the long run. As a Data Scientist specializing in Algorithms, you'll partner closely with product, engineering, and operations leaders to build and scale incentive systems, shape long-term mechanism design strategy, and deliver on critical business goals tied to marketplace efficiency and driver earnings. Candidates with strong optimization backgrounds — think mathematical programming, control theory, or operations research — are a great fit, though we welcome strong candidates from machine learning or causal inference as well. The ideal candidate thrives in a fast-paced environment and brings a hands-on, entrepreneurial mindset to drive results. Responsibilities: Collaborate with engineering and product teams to design, implement, and iterate on new features and algorithmic improvements for driver incentives and pay mechanisms. Design, develop, and deploy optimization models, algorithms, and systems for problems such as budget allocation, multidimensional cost-curve development, and incentive targeting. Write production model code; collabor

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. Driver Incentives Science owns the algorithms and systems behind incentive design, influencing driver engagement and marketplace efficiency — from real-time supply positioning to longer-horizon earnings and engagement programs. The team is responsible for designing pay and incentive mechanisms that are efficient and good for driver experience over the long run. As a Data Scientist specializing in Algorithms, you'll partner closely with product, engineering, and operations leaders to build and scale incentive systems, shape long-term mechanism design strategy, and deliver on critical business goals tied to marketplace efficiency and driver earnings. Candidates with strong optimization backgrounds — think mathematical programming, control theory, or operations research — are a great fit, though we welcome strong candidates from machine learning or causal inference as well. The ideal candidate thrives in a fast-paced environment and brings a hands-on, entrepreneurial mindset to drive results. Responsibilities: Collaborate with engineering and product teams to design, implement, and iterate on new features and algorithmic improvements for driver incentives and pay mechanisms. Design, develop, and deploy optimization models, algorithms, and systems for problems such as budget allocation, multidimensional cost-curve development, and incentive targeting. Write production model code; collabor

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. As a Data Scientist in the Pay, Integrity & 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 & 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. Prior experience in the fintech, fraud or identity space is preferred. Responsibilities: Design and analyze experiments in collaboration with other scientists, product & engineering; communicate findings to stakeholders and facilitate launch decisions Leverage advanced statistical techniques to generate quantitative insights and develop machine learning models Analyze the wide variety of signals available to identify patterns in large datasets and uncover root causes Partner with product managers, engineers, and operators to translate analytical insights into decisions and action Build data pipelines and develop analytical frameworks to monitor business and product performance Set business metrics that measure the health of our products, as well as passenger and driver experience Collaborate with product and engineering and communicate findings to stakeholders in a clear and concise manner Experience: Degree in a quantitative field such as statistics, economics, applied math, operations research or engineering (advanced degrees preferred), or relevant work experience 4-6+ years of industry experi

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. 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. 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. 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. 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: Design rigorous experiments and quasi-experiments to measure the causal impact of SCC product and AI-agent launches, and drive data-informed launch decisions. 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. Quantify the long-term effects of support-experience changes on rider and driver retention, and uncover heterogeneous treatment effects across our community. Deliver strategic insights on quality–cost tradeoffs, empowering leadership to balance service quality, coverage,

Our Purpose Mastercard powers economies and empowers people in 200&#43; countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Lead Data Scientist Overview: Services within Mastercard is responsible for acquiring, engaging, and retaining customers by managing fraud and risk, enhancing cybersecurity, and improving the digital payments experience. We provide value-added services and leverage expertise, data-driven insights, and execution. The Cyber and Intelligence Solutions team is responsible for innovation, development and management of our products and services to address evolving risk and security needs for all of Mastercard’s customers across the world including Banks, Merchants, Fintechs and of course consumers. The Lead Data Scientist will be a key contributor in helping Mastercard develop and deliver actionable insights and products to help issuers, acquirers and merchants reduce fraud. What will you do? -You will be a key player in helping Mastercard extract value from existing data sources in order to better understand, detect and prevent fraud. -Use your data science expertise and skills to analyze worldwide fraud data to gain insights regarding fraud. -Apply modeling techniques to identify and understand fraud to protect the MasterCard payment network. -Build and manage new fraud related products and services that will provide value to our customers and increase revenue. All about you: <br

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit’s Ads Data Science team is looking for a highly experienced Staff Data Scientist to advance the intelligence powering the advertiser experience on Reddit. In this role, you'll take deep ownership of a high-impact problem space within advertising, specializing in measurement, identity, and signal quality. This is a high-impact, high-autonomy role where you'll influence strategic direction, set a high technical bar, and drive cross-functional initiatives across one or more critical focus areas in the Ads organization. Responsibilities: Design the Future of Ads Identity: Develop/employ probabilistic models for identity resolution. Design the methodology that links on-platform and off-platform actions to maximize addressability while honoring privacy. Advance Lift Methodologies & Experimentation: Own the statistical rigor behind Reddit’s Brand and Conversion Lift products. Innovate experimental design and develop infrastructure that supports large-scale, high-velocity, low-bias testing for advertisers. Maximize Signal for Predictive Performance: Define the strategy for new signal sources. You will mathematically quantify the value of these signals and work with modeling teams to incorporate them into predictive models, directly improving bidding efficiency and ROAS. Define Ground Truth & Evaluation Frameworks: Solve the industry-wide challenge of validating identity and measurement. Design the objective functions and truth sets used to train our models and measure the incremental impact of our identity graph.

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? Evaluation is critical to making progress in scaling intelligence. As models continue to become superhuman in many real-world use cases, we must continue to develop new evaluation techniques that accurately reflect what models are already capable of, as well as set the agenda for what future models should be capable of. In this role, you are responsible for creating these next-generation evaluation methods and infrastructure to measure LLM progress. As a Senior Research Scientist, Model Evaluation, you will: Create ambitious new evaluation benchmarks that push the limits of what our models can accomplish. Work on highly cross-functional teams to translate model feedback into trustworthy, repeatable evaluations. Conduct research to advance the state-of-the-art in LLM evaluation methods, including training LLM judges; refining LLM-based data synthesis pipelines; and improving evaluation efficiency. Build scalable and reusable tools for digging into model performance. You may be a good fit if: You enjoy rapidly building prototypes that demonstrate the boundaries of what LLMs are capable of, and you have developed res

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. This is a hybrid role. It requires going to the local office 3 times a week. The Auth0Lab Team We are a small team of engineers exploring new Auth0 products and features ideas. We take things from 0 to 1 and we look to shape the future of identity. Our team has had a big role shaping the identity industry: we were all early at Auth0, which shaped how devs do authentication as part of Auth0Lab we incubated Auth0 FGA which redefined how authorization is done across the industry and we also incubated Auth0 for AI agents which defined auth for AI agents We are currently focused on enabling builders and companies of any size to ship production grade AI agents, by helping them with identity and security. We believe data, and developing our own models will play a huge role in this. The role We are looking for a Principal Applied AI Scientist to take product ideas from 0 to 1 and define how we do new AI product innovation. You'll have a lot of independence: you set the technical direction for AI, and experiment fast with minimal process. With that comes real ownership: you'll be the first AI/ML person in the team, so you'll often be figuring it out without a research org behind you. This is a hands-on role. Publishing papers and open sourcing results might happen as it helps us and the industry, but is not our main goal. We have a lot to teach you about security, auth, developer products and many other things. And we also want to learn from you. Join us to ha

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit’s Ads Data Science team is looking for a Senior Staff Data Scientist to lead the scientific strategy behind Reddit’s ads measurement and signal systems. This role sits at the center of how Reddit proves advertiser value, improves signal quality, builds privacy-aware measurement systems, and connects ads exposure to real advertiser outcomes. As a Senior Staff Data Scientist for Ads Measurement, you will be the principal architect of our technical vision and the driving force behind the next generation of our measurement ecosystem. In a landscape rapidly shifting due to privacy regulations, browser changes, and evolving platform dynamics, you will spearhead innovation across experimental design (incrementality/lift), identity, signals, and privacy-safe 1P/3P measurement. This is a high-visibility, high-impact role requiring a rare blend of deep experimentation & causal inference expertise, strategic foresight, and the ability to influence cross-functional executives and industry standards. You will not just adapt to the changing ad-tech environment, you will redefine how we measure value. Responsibilities Technical Vision & Strategy: Define the long-term data science vision & strategy across ads measurement, signal quality, identity, attribution, and privacy. Establish how Reddit should evaluate advertiser value, measurement quality, and signal utility across first-party and third-party products. Set the Cross-Pillar Measurement Science Strategy: Define the long-term data science strategy across a

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 and analytics are at the heart of Lyft's products and decision-making. The Metrics team sits in the Central Market Management organization and owns the business metrics that leaders use to run the marketplace. We define these metrics, build and manage the tools and dashboards that make them reliable and easy to access, and drive consistent, standardized definitions across the organization. We are looking for a Data Scientist to join the Metrics team and help shape Lyft's products and decision-making. You will own a domain within the team's surface area, building and maintaining the data and metrics that leaders and partner teams rely on, with significant executive exposure along the way. We want an intellectually curious person with strong attention to detail, a track record of analytical problem-solving, and skilled communication. You will report to a Data Science Manager. Responsibilities Own one or more domain datasets end-to-end, from source data through to the metrics that consumers rely on Build and maintain the processing logic and pipelines that turn raw inputs into trusted, analysis-ready data Own the business metrics derived from that data, developing the deep understanding of the source needed to build each metric correctly Ensure the data is accurate, consistent, and reliable, with quality checks that catch problems before consumers see them Deliver data and metrics to stakeholders in a usable form, and support them as they integrate it into their decisions Partner with product managers, engineers, and operators to translate the data into decisions and action Communicate findings to stakeholders in a clear and concise manner Experience Degree in a quantitative field such as statistics, economics, applied math, operations research, or engineering (advanced degrees preferred), or relev

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. As a Senior Software Engineer, Data on the Mapping team, you will collaborate with our world-class team of engineers, product managers, and scientists to grow and improve the quality of recommended routes and accuracy of our travel time estimations. You will lead the architecture and long-term technical direction of our offline experimentation tooling and route simulation services — the systems that let Lyft test routing changes safely before they reach production. You'll also build scalable data pipelines for experimentation, analytics, and machine learning models, along with the data governance and observability systems that keep them trustworthy. Your work will enable integration with partner teams and allow stakeholders across Engineering, Data Science, and Product to make data-informed decisions that directly impact Lyft’s growth and profitability. Our technology stack is based on the latest technologies such as AWS, Databricks, Kubernetes and Airflow. You will work with incredibly passionate and talented colleagues from software engineering, machine learning and data science on projects that directly impact millions of riders and drivers. Responsibilities Own core data pipelines end-to-end, building deep subject matter expertise in the systems you manage and defining/managing SLAs for pipelines, services, and datasets to ensure reliability at scale Serve as the technical owner and architectural lead for our offline experimentation platform and route simulation services, setting technical direction, evaluating trade-offs, and ensuring the systems scale with Lyft's routing and mapping ambitions Continuously evolve data models and schemas to meet business and engineering requirements Develop AI tools that support self-service management of data pipelines (ETL) and schema evolution, and perform han

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. Our team is dedicated to creating a seamless and secure experience for our riders and drivers, ensuring their identity and data are protected at all times. As a Senior Product Designer, you'll lead the design of solutions that help drivers understand their earnings and get paid securely while protecting our communities from fraud. You will work closely with cross-functional teams, including product managers, designers, engineers, and data scientists, to create intuitive and effective designs on driver payments and complex security challenges. You’ll advocate for a customer-centric approach and thrive in a dynamic, fast-paced environment. From initial ideation through to launch, you'll support projects with interaction, visual, and product thinking skills, helping to define and deliver impactful experiences for our Payment, Identity and Integrity teams. The Opportunity Design features that help drivers understand their earnings, access their pay, and resolve payment issues efficiently Lead end-to-end design for driver earnings and identity verification experiences, from research and ideation through execution Play a critical role in designing solutions that protect our users and enhance their trust in our platform Collaborate with cross-functional partners to design intuitive and effective designs that address unique rideshare driver, identity and fraud challenges Responsibilities: Problem solve, think big, and explore divergent concepts/ideas while understanding how to converge and build iteratively towards your vision. Influence the shape of the product with research and data while executing design work using high quality wireframes, mockups, user journeys, and cross-platform interactive prototypes. Advocate for design by sharing your work and presenting cross-functionally, while being able to

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. As a Frontend Software Engineer on the Operator Core Tooling pod, you'll play a vital role in building the robust services that power our critical operations tooling platform. Your work will directly empower our micromobility operations teams by providing them with intuitive and efficient tools, significantly improving their daily workflows as they manage our fleet. You'll collaborate closely with business leaders, front-end developers, and data scientists across Lyft to achieve this impact. Responsibilities: Help define the roadmap and architecture based on technology and business needs Write well-crafted, well-tested, readable, maintainable code Have a good grasp and ability to explain the various tradeoffs made in decisions Participate in code reviews to ensure code quality and distribute knowledge Lead projects from idea to positive execution Incorporate considerations for business context and failure modes in your work Proactively participate in resolving ongoing incidents Unblock, support, effectively communicate and obtain buy-in across teams to achieve results Share your knowledge by giving brown bags, tech talks, and evangelizing appropriate tech and engineering best practices See the direct impact of your work on the efficiency of our operating teams Experience: 3+ years of software engineering industry Advanced knowledge of JavaScript Experience working with modern JavaScript frameworks, like React Experience working with NodeJS and Express applications Experience working with design systems (e.g. Bootstrap, Salesforce Lightning, GitHub Primer) Good understanding of web performance and how browsers and DOM work Experience with unit, integration, and end-to-end testing Experience designing, building and improving a set of team owned components Culture of investigating and solvin

About the Role: Tubi is seeking a highly skilled and experienced Senior QA Automation Engineer to lead quality assurance initiatives for our cutting-edge streaming and AI-driven product features. This pivotal role involves ensuring exceptional end-to-end user experiences, robust streaming playback, and the accuracy and integrity of our AI/ML features across web, mobile, and OTT platforms. We're looking for a candidate with a strong background in streaming QA and deep technical knowledge of media workflows. You'll be instrumental in collaborating with engineering, product, and data science teams to define comprehensive QA strategies that guarantee both functional excellence and data-level quality. This is a hybrid role based out of our Toronto office. You must be willing to travel to our Toronto office three days/week. What You'll Do: Design and lead test strategies for streaming workflows, playback systems, and AI-powered features. Test across platforms (web, mobile, and connected TV) to ensure functional parity and playback stability. Validate streaming performance—including ABR logic, encoding pipelines, and DRM integrations—under diverse real-world conditions. Debug with precision using tools like Charles Proxy, Chrome DevTools, ADB, and Xcode. Collaborate with data and ML teams to validate AI model updates, recommendations, and personalization accuracy. Leverage AI-assisted QA tools to enhance regression coverage, UI validation, and anomaly detection. Contribute to automation and CI/CD frameworks, driving faster, more reliable releases. Help drive a shift-left testing approach by engaging early in the software development lifecycle, partnering with product managers, engineers, and data scientists to identify quality risks, define test strategies, and ensure testability during requirements and design phases. Oversee QA deliverables for multiple concurrent releases and ensure seamless sign-off for production launches. Monitor live environments for playback or reco