Data Center Infrastructure Architect in Canada

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? This role will focus on evaluating coding tasks, requiring you to review and debug code, navigate repository architecture, and analyze model trajectories. Your work will contribute to our model development efforts and the logic our models apply when completing task requests. Please note : This is a part-time independent contractor position available within Canada. We seek candidates who are able to commit to 16 hours per week minimum at a 40 CAD/hour contract rate. This role is BYOD 💻 - Bring Your Own Device (laptop). Remote work within Canada. 12 month contract. Performance incentives included! As a Data Annotation Specialist, you will: Evaluate the model's ability to respond to coding requests, workflows, and code base-related questions using available tools. Assess agent trajectories and model capabilities for code generation and debugging requests. Prompt models to complete complex coding tasks and review the accuracy of generated responses. Label, proofread, and improve machine-written and human-written software engineering-related outputs. Report quality and performance trends related to model/agent behavio

About Gusto At Gusto, we're on a mission to grow the small business economy. We handle the hard stuff — payroll, health insurance, 401(k)s, and HR — so owners can focus on their craft and their customers. With teams in Denver, San Francisco, and New York, we support more than 500,000 small businesses nationwide and are building a workplace that reflects the people we serve. All full-time employees receive competitive base pay, benefits, and equity (RSUs) — because everyone who helps build Gusto should share in its success. Offer amounts are determined by role, level, and location. Learn more about our Total Rewards philosophy . AI is a fundamental part of how work gets done at Gusto. We expect all team members to actively engage with AI tools relevant to their role and grow their fluency as the technology evolves. AI experience requirements vary by role and will be assessed during the interview process. About the Role: As a Data Scientist supporting Risk, you will play a crucial role in leveraging experimentation, statistical inference, and causal analysis to drive strategic decision making that contributes to the overall success of our organization. The ideal candidate is a trusted data storyteller with strong statistical and coding skills, and a passion for applying these skills to help small businesses thrive. In this role you’ll be working with an established team and risk leaders in Engineering, Product, Design, Operation, Identity and Compliance. You'll define and track metrics that help us understand our business performance, and dive deep into our risk stack data to deliver insights and answer questions. You’ll also integrate AI-assisted practices to accelerate analysis, enhance rigor, and expand the reach of insights across Gusto. This role is an equivalent of Staff-level, with an expectation of owning experimentation and building risk models that will have direct impact on business decisions. This is a San Francisco-based role with exp

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,

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

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

Product Data Management Engineer – Mid-Level, Experienced or Senior — USA - El Segundo, CA. Apply via Workday.

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

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. Lyft Business builds products that help organizations move the people who matter most - employees, customers, patients, and guests - easily and efficiently. Our offerings include Business Travel, Lyft Pass, and Concierge (for healthcare and non-healthcare rides), enabling companies to manage transportation at scale through APIs, integrations (e.g., Concur, Expensify), and dedicated tools. These platforms power high-impact B2B use cases across corporate travel, healthcare access, customer experience, and community programs. We are seeking a Senior Data Scientist to lead technical initiatives across the entire Lyft Business product suite. In this role, you will shape the technical vision, define algorithmic roadmaps, and drive execution for data science projects that accelerate growth, improve operational efficiency, and deliver measurable value to our enterprise partners. You’ll collaborate closely with Product, Engineering, Design, and Go-to-Market teams to build production ML models, experimentation frameworks, and advanced analytics that inform strategy and power product innovation. This is a high-visibility, high-impact role with direct influence on Lyft’s enterprise offerings. The ideal candidate will bring deep expertise in algorithm development, machine learning, causal inference, and experimentation, alongside strong business acumen in B2B contexts and a proven track record of t

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 Growth Products team drives rider and driver acquisition to scale the business and balance the marketplace. We specialize in incentive and messaging targeting, budget optimization, and paid media measurement, and move rapidly to test new ideas and products. As a Data Scientist expert in causal inference and marketing mix models (MMM), you will lead our efforts to measure and optimize investments across marketing channels. Responsibilities: Deliver results across the entire lifecycle of data science solutions for Growth: from defining the problem with cross-functional stakeholders to deploying production models that address key business problems. Own complex domains and develop long-term roadmaps to maximize business impact. Build statistical pipelines, write production code, and design/analyze experiments. Participate in the science on-call rotation to ensure automated campaigns operate successfully. Experience: Advanced degree in statistics, economics, mathematics, or equivalent industry experience. 4+ years of industry experience in causal inference or data science. Proven ability to apply statistics to unstructured problems and deliver measurable results. Deep technical expertise in causal inference and tackling challenging measurement problems. Expertise in marketing mix modeling is highly preferred. Expertise in SQL and experience with large-scale data platforms. Proficiency in Python and working within production coding environments. Benefits: Great medical, dental, and vision insurance options with additional programs available when enrolled Mental health benefits Family building benefits Child care and pet benefits 401(k) plan with company match to help save for your future In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team membe