Scientist Analytical Research And Development in Canada

About the job Artefact is a next-generation data and AI consulting firm dedicated to accelerating the adoption of data and AI to create measurable business impact across the full enterprise value chain.We sit at the intersection of consulting, data science, AI technologies, data engineering, and digital transformation. We do not just advise — we build, implement, and deliver results our clients can measure. Our teams bring together consultants, data scientists, data engineers, AI engineers, analysts, and digital experts to solve complex business challenges with pragmatic, production-ready solutions. As Artefact continues to grow in the US, we are building a team of entrepreneurial data and AI talent who can help clients move beyond experimentation and into scalable, governed, value-generating AI adoption. Who We Are Founded and headquartered in Paris, Artefact is a next-generation consulting firm, specializing in data, analytics & AI consulting, dedicated to transforming data into business impact across the entire value chain of organizations. We are proud to say that we help our clients grow their data and digital capabilities, and that we’re also growing in parallel. We have 2000 employees across 36 offices who are focused on accelerating digital transformation. Our state-of-the-art data technologies, lean AI agile methodologies, and cohesive teams of the finest business consultants, data analysts, data scientists, data engineers, and digital experts are all dedicated to bringing extra value to every client. We design data-based solutions to meet our clients' specific needs, always conceived with a business-centric approach and delivered with tangible results. Our data-driven services are built upon the deep AI expertise we've acquired with our 1000+ client base around the globe. Find out more at artefact.com . What you will be doing Artefact is looking for a Senior AI & Data Scientist: a scientist who owns models end to end, from problem framing thr

About the Team As DoorDash continues to expand rapidly, our Core Consumer team plays a pivotal role in shaping the consumer experience through enhancing personalization, search relevance, merchandising strategy, app quality, and the overall ordering experience. Our mission is to implement scalable data solutions and provide insights that directly influence our strategic product direction. We are looking for an Analytics Senior Manager to lead our Discovery team. About the Role As a Senior Manager of Data Science/Analytics, you’ll be leading a team of data scientists who are working on improving the consumer experience. You will develop strategic insights and work closely with the product, engineering, strategy and operations teams to actively build and measure the impact of new features. You will oversee our metrics and analytics strategy to inform strategic product direction, offer technical leadership and build processes to support velocity, and partner with data and product engineers to build robust data foundations. You're excited about this opportunity because you will… Lead and develop a team of Data Scientists in investigating complex issues and uncovering key drivers of our business, along with your own contributions as an Individual Contributor Influence the Product and Operations roadmap by making actionable recommendations based on data Interface frequently with senior leadership to showcase your team’s work and tackle complex business problems Drive measurement strategy for the area under scope, defining success metrics and implementing best practices around experiment design and statistical analysis Develop a strategic learning roadmap based on data observations, strategic questions, and hypotheses We're excited about you because you have… A degree in Math, Physics, Statistics, Economics, Computer Science, or a similar domain Experience managing a team of data scientists, and a track record of delivering impactful analyses 8+ years of experience i

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 We’re looking for an Engineering Manager to lead the Data Infrastructure team within Statsig Experiment at Amplitude. You will lead a multidisciplinary team of software engineers, data engineers, and data scientists responsible for the systems that power experimentation at scale. The team owns three critical areas: Data ingestion: Collecting and importing experiment exposures, custom events, OpenTelemetry data, and real user monitoring data across SDKs, streaming systems, cloud storage, and customer data warehouses. Data computation: Building distributed computation systems that transform raw data into accurate, timely experiment results. Stats engine: Developing and productionizing the statistical methods that help customers make trustworthy decisions from their experiments. This is not a traditional data engineering management ro

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

The Opportunity Join Enigma's Growth & KYB Team at a pivotal moment as we continue to create sales and marketing solutions for small businesses. We're seeking an experienced Senior Software Engineer to develop and build innovative data products and systems that directly impact our customers and accelerate our growth. Your work will influence decisions for companies that employ half the U.S. workforce, creating tremendous value for our clients. The Role As a member of the Growth & KYB Team, you will: Design, develop and deliver data products that solve critical customer pain points and build scalable, high-quality systems that deliver rich interactions with our data. Engage with software engineers, data scientists, and product managers to create experiences that move a customer from discovery to evaluation to purchase. Analyze and extract value from data at scale, building efficient, maintainable production-grade data solutions. Create scalable and highly maintainable systems deployed in cloud environments. Own architecture and design decisions as well as hands-on implementation, ensuring that customer experiences are compelling and have low costs of ownership. What You’ll Do Operates with a bias for action and knows how to deliver value in the short, medium, and long term. Loves interacting with product teams and works hard to solve customer problems in a repeatable way. Adopts a principled, metrics-driven approach to difficult data problems and demonstrates excellence in their analytics and engineering craft. Operates transparently, collaboratively, and with low ego—loves learning from others and having their ideas questioned and challenged. Has a “can-do” attitude and thrives on a highly collaborative, cross-functional team that plays a critical role in the company’s success. Is eager to own architecture and design decisions as well as hands-on implementation. What Makes This Role Exciting? Impact : Develop products that take an innovative data-first appro

About the Team DoorDash is a data driven organization and relies on timely, accurate and reliable data to drive many business and product decisions. Data is at the foundation of DoorDash success. The Data Engineering team builds database solutions for various use cases including reporting, product analytics, marketing optimization and financial reporting. By implementing data structures and data warehouse architecture, this team serves as the foundation for decision-making at DoorDash. The focus extends to enhancing the developer experience by creating tools that support the organization's high-velocity demands. To lead the growing team of Data engineers we are looking for managers who are passionate about Data and are thought leaders in coaching, guiding and leading teams to make Data a winning edge for DoorDash. About the Role DoorDash is looking for a Data Engineering Manager to guide the development of enterprise-scale data solutions. This manager will also act as a technical expert on all things related to data architecture to empower the greater community of data engineers, data scientists, and DoorDash partners. Your focus extends to fostering an engineering culture of excellence, empowering engineers to deliver reliable, flexible solutions at scale. Additionally, you'll play a pivotal role in building and nurturing a top-performing team, driving innovation and success in a dynamic, fast-paced environment. You must be located in San Francisco, CA, Sunnyvale, CA, or Seattle, WA for this hybrid position. You’re excited about this opportunity because you will… You are a people leader. You thrive in hiring, building, growing and nurturing impactful business focused data teams You are a technology leader. You drive the technical and strategic vision for the embedded pods and foundational enablers to meet current and future needs for scale and interoperability You strive for continuous improvement of data architecture and development process You think of quick wins

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 is looking for an Engineering Manager from across multiple disciplines. We are growing our team with people who want to build, improve, and incorporate technologies that make the lives of our community more enriched. As an Engineering Manager at Lyft, you'll collaborate with other teams and orgs, product managers, designers, data scientists, analysts, and operations on technology that empowers us to iterate quickly, while focusing on delighting our passengers and drivers. The Rider organization is focused on building a seamless, best-in-class rideshare experience for riders. From the foundational functionality of requesting a ride to the tailored interactions with specific verticals like your flight, we sweat the small stuff to help make Lyft the best transportation solution. As an Engineering Manager on the Rider vertical team, you will act as a critical technical leader, taking holistic ownership of supporting current projects and delivering new products from 0 to 1. This includes developing complex systems, defining strategic roadmaps, driving cross-functional alignment, and ensuring engineering excellence to improve the rideshare experience. Responsibilities: Drive team execution, proactively resolve bottlenecks and make decisive trade-offs. Partner with cross-functional teams (Product, Design, Marketing, Science, and Analytics) to define the team's strategic direction. Translate high-level business goals into actionable projects. Own a team roadmap from conception to delivery, managing cross-team dependencies and mitigating risks. Maintain operational excellence through contributing to best practices for observability, reliability, and on-call processes. Ensure technical excellence through architecture reviews, tech debt management, and engineering guidance. Maintain team health

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 an Engineering Manager on the Core Rider team, you will act as a critical technical leader in a highly visible area of the Rider Organization. Taking holistic ownership of our foundational systems and core rider functionality, you will be directly responsible for moving top-line business metrics and delivering a seamless rideshare experience. You will partner with multiple product managers, data scientists, and cross-functional teams to develop complex systems, define strategic roadmaps, scale the product and infrastructure that powers how millions of riders request and experience their rides every day. Responsibilities: Drive team execution, proactively resolve bottlenecks and make decisive trade-offs. Partner with cross-functional teams (Product, Design, Marketing, Science, and Analytics) to define the team's strategic direction. Translate high-level business goals into actionable projects. Own a team roadmap from conception to delivery, managing cross-team dependencies and mitigating risks. Maintain operational excellence through contributing to best practices for observability, reliability, and on-call processes. Ensure technical excellence through architecture reviews, tech debt management, and engineering guidance. Maintain team health by creating and refining team processes, fostering a supportive team culture, and managing resourcing. Develop team member careers by matching them with opportunities, setting clear expectations, and providing timely feedback. Build relationships across engineering teams to share learnings, align on standards, and identify collaboration opportunities. Serve as a dependable, high-bar interviewer and active participant in Lyft’s broader community. Experience: BS/MS or equivalent in Computer Engineering, Computer Science, or a related field, or equivalent practic

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 is looking for experienced software engineers from a variety of disciplines. We are growing our team with people who want to build, improve and incorporate technologies that make the lives of our community more enriched. As an engineer at Lyft, you'll collaborate with teams like product, data science, analytics, and operations on code that empower us to iterate quickly, while focusing on delighting our passengers and drivers. As a Senior Software Engineer on the Marketplace team, you will lead work streams to improve business operations in Lyft’s Marketplace. You'll design AI driven data analytics platforms, data pipelines and metric governance systems that our business leaders use on a daily basis to make key strategic decisions. You will partner with business leaders and data scientists across our organizations to enable running the business more efficiently. Responsibilities: Help define the roadmap and architecture based on technology and business needs Drive AI innovation for business analytics and operations Write well-crafted, well-tested, readable, maintainable code Have a good grasp and ability to explain the various tradeoffs made in decisions Participate in code reviews to ensure code quality and distribute knowledge Lead projects from idea to positive execution Incorporate considerations for business context and failure modes in your work Proactively participate in resolving ongoing incidents Unblock, support, effectively communicate, and obtain buy-in across teams to achieve results Share your knowledge by giving brown bags, tech talks, and evangelizing appropriate tech and engineering best practices Experience: 5+ years of software engineering industry experience with a high level programming language (bonus points for experience with Python or Go) AI Experience in Agen

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career. About the team Stripe processes over $1T in payments volume per year, which is roughly 1% of the world’s GDP. The tremendous amount of data makes Stripe one of the best places to do machine learning. The ML Infra team builds services and tools that power every step in the ML lifecycle, including data exploration, feature generation, experimentation, training, deploying, serving ML models, and building LLM applications. With the phenomenal developments happening in the field of AI, we are positioned to accelerate the adoption of AI/ML across all parts of the company by building highly scalable and reliable foundational infrastructure. What you’ll do You will work closely with machine learning engineers, data scientists, and product engineering teams to enable seamless end-to-end experience in building solutions across data, analytics, and AI/ML platforms. You will build the next generation of ML Infra services and major new capabilities that substantially improve ML development velocity and MLOps maturity across the company. Responsibilities Designing and building scalable, reliable, and secure services for notebooks, ML model training, experimentation, serving, and LLM applications across multiple regions. Creating services and libraries that enable ML engineers at Stripe to seamlessly transition from experimentation to production across Stripe’s systems. Working directly with product teams and ML engineers to improve their day-to-day pr

About Snorkel At Snorkel, we believe meaningful AI doesn’t start with the model, it starts with the data. We’re on a mission to help enterprises transform expert knowledge into specialized AI at scale. The AI landscape has gone through incredible changes since 2015, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler! We’re looking for a Research Scientist to advance how high-quality data and environments for AI agents are created. You’ll build and optimize pipelines that combine real-world data, automated generation, and human expert input. Working with domain experts, academic partners, customers, and our product and engineering teams, you’ll scale these pipelines to target frontier model performance gaps and expand data and environment diversity. Your work will amplify human knowledge and judgement, enabling experts to create and refine data and agentic environments that strengthens Snorkel’s position as the frontier data lab. This role is ideal for someone who wants to advance frontier AI through data and environment creation and enjoys turning research into reusable, scalable systems. Location: San Francisco, New York, OR REMOTE Main Responsibilities Design, implement, and optimize reusable pipelines that combine AI capabilities with expert judgment to accelerate data and agentic environment creation. Design and run rigorous experiments to validate proof-of-concept approaches, measure their impact on data quality, pipeline efficiency, and model performance, and communic

We believe communication belongs to everyone. We exist to democratize phone service. TextNow is evolving the way the world connects, and that's because we're made up of people with curious minds who bring an optimistic yet critical lens into the work we do. We're the largest provider of free phone service in the nation. And we're just getting started. Join us in our mission to break down barriers to communication and free the flow of conversation for people everywhere. TextNow is looking for an experienced Data Developer with hands-on experience designing and developing data platforms. You will own the design, development, and maintenance of TextNow's data platform, enabling us to make effective data-informed decisions. You will be part of cross-functional efforts to build scalable and reliable frameworks that support allTextNow's business and data products. In this role, you can interact with different functional areas within the business and influence decision-making in a fast-growing mobile communications start-up. This role is about impact at scale. You’ll shape how TextNow builds and operates its systems in an AI-first environment where intelligent tooling is embedded into everyday engineering practice. Using AI is not optional, it’s expected. From design and architecture to implementation, testing, debugging, documentation, and operational analysis, you will actively leverage AI tools to increase velocity, improve code quality, and make better technical decisions. We provide a robust suite of AI-powered development tools and workflows to support you, and we expect you to continuously evolve how you use them to raise the bar for efficiency, clarity, and product excellence across the organization. What You'll Do Own TextNow's data warehouse, data pipelines, and integration points between various business systems. Design, develo

Scale Labs, Research Scientist — Agent Robustness As the leading data and evaluation partner for frontier AI companies, Scale plays an integral role in understanding the capabilities and safeguarding AI models and systems. Building on this expertise, Scale Labs has launched a new team focused on policy research, to bridge the gap between AI research and global policymakers to make informed, scientific decisions about AI risks and capabilities. Our research tackles the hardest problems in agent robustness, AI control protocols, and AI risk evaluations to help governments, industry, and the public understand and mitigate AI risk while maximizing AI adoption. This team collaborates broadly across industry, the public sector, and academia and regularly publishes our findings. We are actively seeking talented researchers to join us in shaping this vision. As a Research Scientist working on Agent Robustness you will work on the fundamental challenges of building AI agents that are safe and aligned with humans. For example, you might: Research the science of AI agent capabilities with a focus on how they relate to safety, risk factors, and methodologies for benchmarking them; Design and build harnesses to test AI agents’ tendency to take harmful actions when pressured to do so by users or tricked into doing so by elements of their environment; Design and build exploits and mitigations for new and unique failure modes that arise as AI agents gain affordances like coding, web browsing, and computer use; Characterize and design mitigations for potential failure modes or broader risks of systems involving multiple interacting AI agents. Ideally you’d have: Commitment to our mission of promoting safe, secure, and trustworthy AI deployments in the industry as frontier AI capabilities continue to advance. Practical experience conducting technical research collaboratively. You should be comfortable building and leveraging agent scaffolding, designing evaluation harnesses, an

Scale Labs, Research Scientist — AI Controls and Monitoring As the leading data and evaluation partner for frontier AI companies, Scale plays an integral role in understanding the capabilities and safeguarding AI models and systems. Building on this expertise, Scale Labs has launched a new team focused on policy research, to bridge the gap between AI research and global policymakers to make informed, scientific decisions about AI risks and capabilities. Our research tackles the hardest problems in agent robustness, AI control protocols, and AI risk evaluations to help governments, industry, and the public understand and mitigate AI risk while maximizing AI adoption. This team collaborates broadly across industry, the public sector, and academia and regularly publishes our findings. We are actively seeking talented researchers to join us in shaping this vision. As a Research Scientist focused on AI Controls and Monitoring, you will design methods, systems, and experiments to ensure that advanced AI models and agents remain aligned with intended goals, even in high-stakes or adversarial environments. For example, you might: Develop monitoring techniques and observability methods that track AI behavior in real time to identify and flag deviations, emergent capabilities, or anomalous outputs; Research mechanisms for layered control, including fail-safes, oversight protocols, and intervention methods that can halt or redirect AI systems when risks are detected; Design red-team simulations to probe weaknesses in oversight and control mechanisms, and build mitigations to close identified gaps; Collaborate with policymakers, engineers, and other researchers to establish standards and benchmarks for AI monitoring and escalation. Ideally you’d have: Commitment to our mission of promoting safe, secure, and trustworthy AI deployments in the industry as frontier AI capabilities continue to advance. Practical experience conducting technical research collaboratively. You should be

Scale Labs, Research Scientist — Safety Post Training As the leading data and evaluation partner for frontier AI companies, Scale plays an integral role in understanding the capabilities and safeguarding AI models and systems. Building on this expertise, Scale Labs has launched a new team focused on policy research, to bridge the gap between AI research and global policymakers to make informed, scientific decisions about AI risks and capabilities. Our research tackles the hardest problems in agent robustness, AI control protocols, and AI risk evaluations to help governments, industry, and the public understand and mitigate AI risk while maximizing AI adoption. This team collaborates broadly across industry, the public sector, and academia and regularly publishes our findings. We are actively seeking talented researchers to join us in shaping this vision. As a Research Scientist working on Safety Post-Training you will develop and apply post-training methods and interpretability techniques to make frontier AI systems safer, and better understood by researchers and policymakers.. For example, you might: Design and run post-training pipelines to study how training choices affect model safety, robustness, and alignment properties; Develop interpretability-informed evaluations that reveal how and why models produce unsafe, deceptive, or otherwise undesirable behaviors, and use those insights to guide targeted mitigations; Collaborate with policymakers, engineers, and other researchers to translate post-training and interpretability findings into actionable safety standards, evaluation benchmarks, and best practices. Ideally you’d have: Commitment to our mission of promoting safe, secure, and trustworthy AI deployments in the industry as frontier AI capabilities continue to advance. Experience with post-training and RL techniques such as RLHF, DPO, GRPO, and similar approaches. A track record of published research in machine learning, particularly in generati