Data Analytics Manager 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. Interns work side-by-side with top engineers in the industry while having autonomy from the get-go. They contribute to user-facing products and are able to see their work go live quickly. Lyft fosters a collaborative environment in the office, so there's always a sharp mind eager to hear about your next idea. So what's yours? Responsibilities: Own your project, while checking in with other team members throughout the day with questions and updates You leave the code in a better state than when you found it (progressive refactor) You value reliability, ensured by testing Participate in code reviews to ensure code quality and distribute knowledge Continuous integration and deployment Go home knowing that your work today is meaningfully improving the lives of every Lyft driver and every Lyft passenger! Experience: Currently pursuing a Bachelor's or Master's degree in Computer Science, Data Science or related major from a university in Canada (required) , with a graduation date between December 2027 and Summer 2028 (required) . For any candidates who are master's students who worked between their bachelor's and master's programs: candidates should also have less than 2 years of relevant full-time work experience Available during Summer 2027 for an internship in Toronto Strong knowledge of CS fundamentals Knowledge of SQL and data modeling fundamentals Experience working with databases Excellent communication skills Interest in solving large scale data problems in a real world scenario Passion for community, sustainability, 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 belie

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. 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

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

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

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.

About Forma.ai: Forma.ai is a Series B startup that's revolutionizing how sales compensation is designed, managed and optimized. We handle billions in annual managed commissions for market leaders like Edmentum, Stryker, and Autodesk. Our growth has been fuelled by our passion for fundamentally changing and shaping how companies use sales intelligence to drive business strategy. We’re welcoming equally driven individuals who are excited about creating something big! About the Team Engineers on this team construct our rules-based calculating engine for processing sales commissions. This might sound simple if you have never been exposed to sales comp plans, it is not! We are low on meetings, high on accountability. Most of the team are in EST time zone but we have a few located in PST and Central as well. We are far from maintenance / progressive evolution in many areas, there is a lot of room to make a big impact in the overall design. What you’ll be doing Reporting to the Manager of Data Platform, you will play a critical role in the evolution of our Spark based data platform. You'll lead development efforts for our complex, data-rich platform features while being an example to the team of code quality and thoughtful software design. You will be working on the most challenging code at Forma. As a Staff Engineer, you are expected to operate with a high degree of ownership and trust. This includes proactively identifying architectural risks, surfacing edge cases or constraints others may not see, and advocating for improvements that strengthen the long-term integrity of the system. We value engineers who bring forward thoughtful perspectives - even when they challenge assumptions - and who help the team see around corners. You will: Design and evolve backend services that power product workflows. Architect data models representing hierarchical & graph structures, relationships, and large-scale enterprise datasets. Build

About Forma.ai: Forma.ai is a Series B startup that's revolutionizing how sales compensation is designed, managed and optimized. We handle billions in annual managed commissions for market leaders like Edmentum, Stryker, and Autodesk. Our growth has been fuelled by our passion for fundamentally changing and shaping how companies use sales intelligence to drive business strategy. We’re welcoming equally driven individuals who are excited about creating something big! About the Team Engineers on this team build our rules-based calculation engine for processing sales commissions. This might sound simple if you have never been exposed to sales compensation plans, it is not. We are low on meetings and high on accountability. Most of the team is in the EST time zone, with a few located in PST and Central as well. We are still evolving many areas of the platform, which means there is meaningful room to improve the design, reliability, and scalability of the systems we build. What you’ll be doing Reporting to the Manager of Data Platform, you will play an important role in the evolution of our Spark-based data platform. You’ll design and build data-rich platform capabilities, contribute to system design discussions, and help ensure our data systems remain reliable, maintainable, and scalable as Forma grows. As a Senior Engineer, Data Platform, you are expected to operate with strong ownership and sound technical judgment. This includes identifying risks in the work you own, surfacing edge cases, asking thoughtful questions, and proposing improvements that strengthen the quality and reliability of the platform. You will: Design, build, and improve Spark-based data pipelines and platform services. Work with complex data models representing sales compensation plans, hierarchies, relationships, and enterprise datasets. Build reliable, deterministic data systems that customers and internal teams can trust. Improve testing, observability, data quality,

Level Up Your Career with Zynga! At Zynga, we bring people together through the power of play. As a global leader in interactive entertainment and a proud label of Take-Two Interactive, our games have been downloaded over 6 billion times—connecting players in 175+ countries through fun, strategy, and a little friendly competition. From thrilling casino spins to epic strategy battles, mind-bending puzzles, and social word challenges, our diverse game portfolio has something for everyone. Fan-favorites and latest hits include FarmVille™, Words With Friends™, Zynga Poker™, Game of Thrones Slots Casino™, Wizard of Oz Slots™, Hit it Rich! Slots™, Wonka Slots™, Top Eleven™, Toon Blast™, Empires & Puzzles™, Merge Dragons!™, CSR Racing™, Harry Potter: Puzzles & Spells™, Match Factory™, and Color Block Jam™—plus many more! Founded in 2007 and headquartered in California, our teams span North America, Europe, and Asia, working together to craft unforgettable gaming experiences. Whether you're spinning, strategizing, matching, or competing, Zynga is where fun meets innovation—and where you can take your career to the next level. Join us and be part of the play! Position Overview: The Senior Director, Data Platform will lead Zynga's centralized data platform and product strategy, managing one of the largest data footprints in the gaming industry—billions of daily gameplay events flowing through a cloud-native stack spanning real-time ingestion, a petabyte-scale warehouse, experimentation, and a self-serve metrics and AI platform. Operating with high autonomy and direct executive sponsorship, you will act as a pathfinder: empowering our global studios to extract maximum value from central data and transforming the group to an AI-first way of working. This highly visible role is based in Toronto and partners closely with studio leaders, central teams, and executives across Zynga's global labels. Relocation support is available. What You'll Do: Craft data product strategy:

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 Infrastructure team is passionate about building software to solve problems at massive scale. We do this often, and when we believe our solution is worth sharing with the community, such as Envoy Proxy , we open source our ideas for the benefit of others. As a Infrastructure Engineer at Lyft, you will run our Production Infrastructure by monitoring system availability and take a holistic view of our platform health. You will build software and platforms to automate infrastructure platform operations and management. By measuring and monitoring our operations you will seek opportunities to optimize our systems in order to push our platform forward, anticipating our customers' needs in order to continually improve the platform. You will provide Lyft partner teams with operational support to help them build robust large scale distributed systems. About the Team Data Pipelines is at the heart of all critical data flowing through Lyft supporting hundreds of services that impact millions of drivers and passengers every day. Our team’s mission is to empower Lyft engineers to self-serve in building and maintaining data pipelines as needed to support products that deliver the world’s best transportation experience. We leverage a variety of technologies to store, stream and manage data making it available to our internal customers. Responsibilities: Maintain and analyze metrics from; operating systems; control planes; and applications to assist in fault detection and performance enhancement Design, develop and deploy tooling and systems that continually improve the reliability, scalability and efficiency of our platform Balance feature development speed and reliability with service-level objectives Operate and improve our Infrastructure using industry best practices and tools Participate in design and

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! Who are we? Our mission is to scale intelligence to serve humanity. We're training and deploying frontier models for developers and enterprises who are building AI systems to power magical experiences like content generation, semantic search, RAG, and agents. We believe that our work is instrumental to the widespread adoption of AI. 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. We like to work hard and move fast to do what's best 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 co-headquartered in Toronto and San Francisco, with key offices in London, New York City, Montreal, Seoul, Germany and Paris. Why this role? We're hiring a People Operations Manager to own our People data and the reporting built on top of it, alongside a slice of the operational work that generates it. Cohere is scaling fast and leadership needs numbers they can trust. Today those numbers take too long to produce and they don't

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! As a Senior Member of Technical Staff specializing in web data for pre-training, you will play a pivotal role in developing the large scale web data pipeline that underpins Cohere’s advanced language models. In this role, you will work extensively with large-scale web corpora, transforming raw, noisy internet data into high-quality training data for pretraining. You will own key components of the data pipeline, including extraction, parsing, deduplication, and filtering. You will also analyze the composition and quality of web data, study its impact on downstream model performance, and collaborate closely with the broader data and evaluation teams to iterate on the training corpus. Your work will be essential to Cohere’s mission of delivering efficient and reliable language understanding and generation capabilities, driving innovation in natural language processing. If you are passionate about transforming data into the foundation of AI systems, this role offers a unique opportunity to make a meaningful impact. Please Note: We have offices in London, Paris, Toronto, San Francisco and New York but also embrace being remote-friend