Data Solutions And Validation Sr Specialist 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. 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 ( Opera

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. 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. 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. 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. 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

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

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 Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . Pinterest is the world's leading visual search and discovery platform, serving over 500 million monthly active users globally on their journey from inspiration to action. As we scale experiences in a complicated ecosystem, ensuring they are safe, fair, and trustworthy is paramount. We are looking for a Senior Data Scientist to help lead Pinterest's Trust and Safety mandate by designing the foundations for measuring the prevalence of unsafe content across the platform. In this role, you will design and build sampling frameworks, complex data aggregations, and measurement methodologies to track Trust & Safety policy violations across complex, multi-component user interactions. You will work in a highly collaborative and cross-functional environment, partnering with ML Engineers, Trust & Safety Ops, subject matter expert teams, and Product

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,