Data in Canada

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,

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. We are looking for an experienced and highly motivated Data Scientist to join the Central Market Management team and lead key initiatives that enhance the quality of our overall decision-making. You’ll work cross functionally with other Data Scientists, Data Analysts, Product Managers, and Finance partners to make sure we are making the most financially efficient decisions to scale our business. You will identify gaps in our operational processes and measurements, and work to create strategies, frameworks, and models to help address them and deliver impact. Responsibilities Leverage data and analytical frameworks to identify opportunities for improving operational efficiency Define and implement decision frameworks, measurement strategies, and scientific methodologies that bring consistency and rigor to business decisions and forecasts, balancing opportunity and uncertainty Deliver integrated, high-quality analytical outputs spanning multiple projects while navigating ambiguity, cross-team dependencies, and open-ended scope Define and implement a robust attribution framework to evaluate the performance of high-stakes decisions Act as a technical lead, guiding other Data Scientists and fostering a culture of analytical excellence Write efficient, clean, production-level code (Python, SQL), ensuring reproducibility, documentation, and long-term maintainability of analytical assets B

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 Driver Earnings team at Lyft is responsible for managing our suite of driver earnings products, driving top business goals around financial metrics and marketplace performance. The team develops and improves automation & execution of driver earnings products, develops new earnings products, and manages financial performance of these products to manage the growth of the business. We are looking for an analyst to join the team that is responsible for working with cross-functional stakeholders to analyze and improve existing earnings products and manage the products’ financial outcomes within the broader Marketplace organization. You will influence existing and future strategy with your data analysis, insights, and storytelling to deliver strategic recommendations on experimentation and product improvements. We’re looking for a data & process-driven individual who has extraordinary attention to detail and a track record of analytical problem-solving. Responsibilities: Support marketplace operations to provide world-class analysis, product recommendations, and reporting to stakeholders. Become an expert in marketplace trends and support weekly reporting structures for the Rideshare organization. Develop domain-specific subject matter expertise in our lever portfolio and support cross-functional initiatives to improve existing products and develop new ones. Analyze marketplace product & financial levers and provide cross-functional teams with actionable insights on improvements and problem areas. Operate within Rideshare decision-making frameworks with a critical lens, evaluating areas of improvement and business growth opportunities. Prepare regular business reviews for leadership, highlighting key areas of focus. Work with stakeholders and other teams to track, report, and r

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 is at the heart of Lyft Business's products and decision-making. We're looking to hire a Data Analyst to build the tools and analytics that drive revenue for the sales organization behind Lyft's B2B portfolio — a multi-billion-dollar book of business spanning healthcare, business travel, corporate commute, automotive, and transit. This team has real say in what gets built. You will be the analytical partner to our Sales and account teams — someone who can translate findings into a clear narrative for both technical and non-technical audiences. Responsibilities: Build the tools and analytics sales leaders use to grow their accounts — pacing views, account-health signals, territory and segment views that change what a rep or manager does next Field requests from Sales, Product, Finance, Legal, leadership, and external stakeholders, and decide what's worth building, what's worth a sharp piece of analysis, and what's out of scope Build and maintain production data pipelines, and automate recurring workflows, with documentation and validation clear enough that a teammate — or an AI agent — can use them without asking you first Define what the team's core metrics mean and where they live, so every dashboard, report, and tool returns the same answer to the same question Contribute to the internal tools and semantic layer — prompts, context, and guardrails — that let stakeholders query B2B data in natural language and trust what comes back Translate insights into a cohesive narrative and present technical findings to senior leadership and non-technical audiences Experience: Degree (or related work experience) with a focus in analytics, statistics, economics, computer science, or other quantitative fields 3+ years of experience in a data analytics or business intelligence role, ideally supporting a sales

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 People Analytics team at Lyft exists to build data trust — turning people data into clear, reliable insights that help our HR Business Partners, talent leaders, and executives make better decisions. We're a small, high-impact team in the middle of a meaningful BI transformation: we recently moved to ThoughtSpot as our primary analytics platform, and we're not just replicating old dashboards — we're rethinking what self-service analytics looks like for a People team. That includes exploring ThoughtSpot's AI capabilities to surface proactive insights, enable natural language querying, and reduce the friction between a business question and a data answer. There's real greenfield work here, and we're looking for someone who wants to help define what AI-powered people analytics looks like at Lyft. We're looking for a Data Analyst to join our People Analytics team, based in Toronto. You'll report to the Senior Manager, People Analytics and serve as the first point of contact for incoming data requests across the People organization — triaging, scoping, and delivering on analytical needs ranging from quick ad-hoc pulls to fully built ThoughtSpot dashboards. This role is well-timed: you'll be joining as we complete our migration from Tableau to ThoughtSpot, which means you'll have genuine influence over how we build our reporting layer and push into ThoughtSpot's AI features — think natural language search, AI-generated insights, and proactive anomaly detection applied to people data. This isn't a "maintain the dashboard" role. It's a chance to help build something new. You'll be a self-starter who is equally comfortable writing SQL and presenting findings to a VP. Responsibilities: Serve as the first point of contact for incoming data requests from across the People organization — scoping needs, setting

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 Engineer on the SCC team, you will have ownership over the data modeling and pipelines that power SCC’s Associate and AI Agent Platform . Your efforts will be critical to the reliability of our pipelines, execution of third party data integrations, accurate reporting of agents performance, and efficiency improvements that can save millions of dollars / year. You will work cross-functionally to bridge Lyft's business goals with data engineering. Your efforts will allow access to business and user behavior insights, using huge amounts of Lyft data to fuel several teams such as Analytics, Data Science, Engineering, and many others. Responsibilities: Owner of the core data pipeline, responsible for scaling up data processing flow to meet the rapid data growth at Lyft Evolve data model and data schema based on business and engineering needs Implement systems tracking data quality and consistency Develop tools supporting self-service data pipeline management (ETL) SQL and MapReduce job tuning to improve data processing performance Write well-crafted, well-tested, readable, maintainable code Participate in code reviews to ensure code quality and distribute knowledge Collaborate cross-functionally with product, engineering, data science, and marketing teams to understand business problems and align on prioritization and solutions Experience: Bachelor's degree in Compute

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 Business's products and decision-making. We're looking to hire a Data Analyst to support our Self-Serve segment — the fastest-growing part of Lyft's B2B portfolio, serving small and mid-size businesses across North America. This is a hands-on role for an analyst who is energized by turning product and customer data into insights that shape strategy — and who builds those insights on a foundation others can trust and reuse. You will be the dedicated analytical partner to the Self-Serve product team, measuring how new features — a redesigned signup experience, onboarding improvements, and lifecycle campaigns — drive customer activation and growth. You'll own the funnel from acquisition through engagement, define the metrics that matter, and deliver the insights that inform where the business invests next. The ideal candidate pairs analytical rigor with a builder's instinct — turning recurring questions into well-defined, reusable datasets instead of one-off answers — and can translate findings into a clear narrative for both technical and non-technical audiences. Responsibilities: Produce high-impact analyses on Self-Serve performance that directly inform product and go-to-market strategy Own the Self-Serve funnel — acquisition, signup, onboarding, and engagement — building the dashboards and datasets that give the team real-time visibility into product health Define what the team's core metrics mean and where they live, so every dashboard, report, and tool returns the same answer to the same question Partner closely with Product and Engineering to validate instrumentation and surface data gaps before they distort the funnel or new features launch — catching the data quality issues that stay invisible until someone goes looking Turn recurring reporting into w

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 & Analytics is at the heart of Lyft's products and decision-making. The Rider Experience team sits at the center of how millions of riders discover, choose, and return to Lyft. We are hiring a Data Science Manager to lead our Toronto-based science & analytics team that turns rider behavior into product strategy. This role owns the analytical foundation behind our most consequential rider-facing decisions: how we measure experience quality, where friction costs us retention, and which bets move rider LTV. You will set the measurement and experimentation standards for rider product squads, and translate ambiguous business questions into rigorous, decision-ready analysis that shapes roadmap and investment. You will also lead the team's transition to AI-native data science and analytics workflows, embedding AI tooling into how we explore data, make decisions, and ship products. Responsibilities: Lead and grow a high-performing team of data scientists and analysts with diverse backgrounds Define and drive the data science vision, strategy, and roadmap, aligning with business and product objectives to improve market competitiveness and rider experience Provide strong technical guidance and coaching to the team on complex data science problems Champion data-driven decision-making and prioritization by partnering with product managers, engineers, marketers, and leaders to translate insights into decisions and action Lead deep-dive analyses into large-scale datasets to identify opportunities for improving rider app experience and overall rider product health Ensure robust experimentation and causal inference methodologies are applied to measure the impact of new features and strategies Mentor and guide the professional and technical development of your team members; help develop the

About Us Twitch is the world’s biggest live streaming service, with global communities built around gaming, entertainment, music, sports, cooking, and more. It is where thousands of communities come together for whatever, every day. We’re about community, inside and out. You’ll find coworkers who are eager to team up, collaborate, and smash (or elegantly solve) problems together. We’re on a quest to empower live communities, so if this sounds good to you, see what we’re up to on LinkedIn and X , and discover the projects we’re solving on our Blog . Be sure to explore our Interviewing Guide to learn how to ace our interview process. About the Role Join the Monetization team at Twitch, where we build the products that help creators make a living on the platform. You'll work on products like Subscriptions, Bits, and Gifting, and the pricing and packaging decisions behind them. You'll partner closely with product, engineering, finance, and data teams to measure the impact of new features, design and analyze experiments, and apply causal inference methods to inform decisions where A/B testing isn't possible. The work ranges from high-velocity experimentation on consumer-facing products to deeper pricing, policy, and segmentation analyses where causal identification is the central challenge. This role is well-suited for someone with a strong economics or causal ML foundation who wants to apply rigorous statistical thinking to real product decisions at scale. You'll need to be comfortable writing SQL, working with imperfect data, and partnering with stakeholders to turn analysis into product impact. Our team is based at Twitch HQ in San Francisco, CA. You can work in San Francisco, CA; New York, NY; or Seattle, WA You Will: Apply causal inference methods where experimentation isn't feasible Develop models and analyses that inform pricing, segmentation, and revenue optimization Design, run, and analyze A/B experiments Pa

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

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. The Data Enablement Team Auth0 is an easy-to-implement authentication and authorization platform designed by developers for developers. We make access to applications safe, secure, and seamless for the more than 100 million daily logins around the world. Our modern approach to identity enables this Tier 0 global service to deliver convenience, privacy, and security so customers can focus on innovation. Within the Data organization, the Data Enablement team is chartered with creating scalable semantic models that make it safe for anyone to see and understand data. By partnering with product and engineering leaders, this team owns the data lifecycle from strategy to prototyping to implementation, executive dashboard and product level self-service support. The Senior Data Analyst Opportunity Reporting to the Manager, Data Enablement - this role will be responsible for unlocking analytics across the company. You will do this through a combination of data lifecycle ownership, data tooling enablement and outreach programs designed to foster the safe usage of scalable data models for reporting and analytic consumption. You'll serve as a critical data and technical partner that empowers our Sales, TAM, and Customer Success teams with the deep product insights they need to succeed. An average week will find you partnering with these teams to understand their measurement needs, reviewing engineering plans to ensure we capture critical data signals from the Auth

Join us in building the future of finance. Our mission is to democratize finance for all. An estimated $124 trillion of assets will be inherited by younger generations in the next two decades. The largest transfer of wealth in human history. If you’re ready to be at the epicenter of this historic cultural and financial shift, keep reading. About the team + role We are building an elite team, applying frontier technologies to the world's biggest financial problems. We're looking for bold thinkers. Sharp problem-solvers. Builders who are wired to make an impact. Robinhood isn't a place for complacency, it's where ambitious people do the best work of their careers. We're a high-performing, fast-moving team with ethics at the center of everything we do. Expectations are high, and so are the rewards. Our Core Data Engineering team is responsible for designing and building all foundational datasets used across Robinhood and within our operational business areas. We build the foundational data models and core data layers that are consumed by downstream users, ensuring high data quality and reliability. We also develop internal data and AI tooling that enables teams across the company to scale their data development workflows efficiently. Our team collaborates with engineering, product, brokerage, crypto, and marketing teams to expand and grow Robinhood's products around the world ! We also partner with Machine Learning teams to build robust training datasets that power intelligent product features. As the Engineering Manager for our Toronto Data Engineering team, you will lead a team of exceptional engineers and drive the execution of key data initiatives. In this role, you will balance technical leadership with people management, dedicating approximately 60% of your time coaching and 40% to hands-on technical contributions, such as code and architecture reviews. You will drive roadmap planning and establish clear goals for the team, particularly as we expand into new mark

About the Role: We're hiring Senior and Staff Data Platform Engineers to join the Data Infrastructure teams in Toronto. Together these teams own the infrastructure that processes billions of events per day: Spark-on-Kubernetes, Flink and Kinesis pipelines, a multi-petabyte Delta Lake, a large-scale MemoryDB feature store, Databricks multi-environment operations, and the catalog and lifecycle systems that govern it. The team is small and senior. Each engineer owns major platform components: you design it, build it, and support it in production. This is a hybrid-role based out of our Toronto office. You must be willing to travel to our Toronto office two days/week. What You'll Do: Spark-on-Kubernetes — EKS-based compute platform for Spark workloads: cluster configuration, Pod Identity IAM, job environment setup, Kustomize overlays, and shadow canary validation Event ingestion — Rust services and Flink jobs processing billions of events per day over Kinesis; throughput, reliability, on-call response, and AI-assisted operational tooling to reduce toil Platform infrastructure — Terraform modules for environment provisioning, cross-account AWS IAM, ARC runner infrastructure, and CI/CD for data platform changes Feature store and ML compute — Flink-based real-time feature pipelines feeding a large-scale MemoryDB cluster; GPU capacity governance and Databricks multi-environment operations for ML training workloads Workflow orchestration and CDC — Airflow-based DAG deployment, change data capture pipeline operations, and data quality monitoring Your Background: 3+ years building and operating production data platform infrastructure at the cluster or platform level, across Spark, Flink, Kinesis, Kubernetes, or equivalent Deep experience in at least one of: Spark-on-K8s cluster operations, Rust-based data or systems engineering, Kubernetes platform engineering and IaC, or data catalog and governance tooling Production AWS experience or equivalent: EKS, S3, Kinesis, and mu

**English version below** Doit être local à Montréal Vous souhaitez travailler dans le domaine de la technologie au sein d'une banque d'investissement? Nous recherchons une personne pour rejoindre une équipe dynamique en tant qu’ Ingénieur(e) Data pour l’un de nos clients. Ce poste est destiné à un rôle d’ingénierie des données au sein de l’équipe MongoDB et Kafka . Nous sommes un groupe hautement technique qui réalise simultanément divers projets pour plusieurs secteurs d’activité. Les responsables métier et les experts sont répartis à l’échelle mondiale, ce qui rend de solides compétences en communication essentielles pour ce poste. Le ou la candidat(e) travaillera en étroite collaboration avec nos partenaires informatiques afin d’analyser les besoins métier et de mettre en œuvre les solutions répondant à ces exigences. À propos de mtrois : Depuis 2010, mtrois aide ses clients à résoudre leurs défis commerciaux et technologiques. Nous sommes une société de conseil en technologie et en affaires avec une main-d'œuvre mondiale qui réalise des projets commerciaux et informatiques significatifs dans certaines des plus grandes organisations de services financiers du monde. Services principaux Consulting et Conseil Services gérés Programme de diplômés Alumni Programme Alumni Pro Nous avons une présence mondiale et sommes experts dans la fourniture d'une qualité exceptionnelle à notre base de clients, offrant des services de conseil dans les domaines du risque, de la réglementation et de la conformité ; Produits des fournisseurs ; Support d'application ; Développement d'application ; Cyber et sécurité de l'information ; Science des données et DevOps. Notre programme Expert offre aux professionnels expérimentés l'accès à des rôles de premier plan dans la technologie, la finance, l'aviation et l'assurance. Rejoignez-nous pour travailler sur des projets technologiques révolutionnaires, des plateformes de trading internationales aux applications critiques pou

Amplitude is the leading AI analytics platform, helping over 4,700 customers—including Atlassian, Burger King, NBCUniversal, and Square—build better products and digital experiences. With powerful AI Agents embedded across our platform, teams can analyze, test, and optimize user experiences faster than ever. Ranked #1 across multiple categories in G2’s Winter 2026 Report, Amplitude is the best-in-class solution for product, data, and marketing teams. Learn more at amplitude.com . As an organization, we deliver for our customers by living our values. We operate from a place of humility, take ownership of problems and successes, approach challenges with a growth mindset, and put our customers at the center of everything we do. Amplitude’s Commitment to Diversity Equity & Inclusion (DEI): Amplitude believes that diversity enables the creation of better products, improves the ability to solve complex problems, and drives more powerful solutions. We strive to create an environment of inclusion—one focused on psychological safety, empathy, and human connection—that will allow employees of all backgrounds to thrive. About The Role & Team Amplitude is only as useful as the data inside it. The Data Warehouse and Integrations team owns how that data gets in and out — importing behavioral and customer data from cloud data warehouses like Snowflake, Databricks, and BigQuery, from cloud object storage like S3 and Azure Blob Storage, and pushing enriched event data back out to warehouses, object storage, streaming destinations, and downstream advertising and marketing platforms. That means batch and streaming pipelines moving billions of events a day, connections that have to keep working across dozens of customer-controlled systems, credentials and configuration that have to stay correct and secure, and latency and reliability targets that customers build their own pipelines on top of. Recent work includes launching new warehouse export destinations, migrating our import