Lead Data Scientist
Design, build, and scale production-grade generative and agentic AI solutions to drive business impact. Lead model development and deployment across cloud platforms while mentoring a high-performing data science team.
Remote Data Scientist Jobs in Canada
82 Data Scientist jobs in Canada available for remote work from home. Apply for positions such as Lead Data Scientist, Senior Data Scientist, Senior Data Scientist, RIsk and more! Discover the best work-from-home or hybrid, full- and part-time jobs.
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Design, build, and scale production-grade generative and agentic AI solutions to drive business impact. Lead model development and deployment across cloud platforms while mentoring a high-performing data science team.
Own and ship end-to-end machine learning models for vendor matching, order routing, and supply chain optimization. Implement decision logic for agentic AI and quantify the business impact of data science initiatives.
Develop advanced ML-based fraud and risk models to reduce financial loss and safeguard user funds. Collaborate across Risk, Compliance, and Product teams to create risk signals and automate decision-making tools.
Apply data science to complex product and business problems by evaluating performance and generating actionable insights. Establish analytical processes, monitoring frameworks, and automated ETL workflows to maintain product quality.
Lead the design and delivery of high-impact decision science systems including forecasting, optimization, and recommendation engines. Establish modeling standards and mentor senior and mid-level data scientists to build the organization's decision science function.
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Develop data infrastructure and production-ready models to accelerate the investment process for hedge funds and family offices. Partner with investment teams to turn large datasets into actionable insights and build portfolio company dashboards.
Lead the experimentation engine and analytics strategy for a high-growth business segment to drive performance and investment decisions. Build reporting backbones and provide driver-based insights on revenue and margin performance to executive leadership.
Design and deliver end-to-end advanced analytics solutions, including churn prediction and customer lifetime value models, to support decision-making. Translate complex data outputs into actionable recommendations through storytelling and visualization for diverse stakeholders.
The role involves collecting, cleaning, and validating data from various sources to generate reports and dashboards. Additionally, the candidate will support automation workflows and AI-powered data processes using APIs from platforms like Google, Meta, and TikTok.
Design, develop, and deploy machine learning models and predictive analytics solutions to support strategic business decisions. Collaborate with engineering and business teams to build scalable data pipelines and mentor junior data scientists.
Lead the end-to-end delivery of advanced statistical and machine learning models for credit risk, pricing, and fraud. Partner with cross-functional teams to integrate these models into applications and mentor team members on technical standards.
The role involves analyzing diverse datasets to optimize underwriting, pricing, and cyber risk selection. You will develop statistical and machine learning models to provide data-driven insights and automate underwriting workflows.
Build, deploy, and maintain production systems for measurement products including MMM and Recommendation Systems. Translate statistical methodologies into scalable customer-facing capabilities while collaborating across engineering and product teams.
Lead high-priority initiatives to build and maintain data models and machine learning models that support the Commercial team and AI Voice Agent program. Collaborate with cross-functional stakeholders to design experiments and create reporting dashboards that impact the company's north star metrics.
Lead the strategy and technical execution of marketing intelligence to optimize B2B and B2C growth. Define the long-term technical roadmap for marketing measurement and quantify the incremental impact of spend using MMM and MTA systems.
Design, build, and deploy machine learning models and AI-driven solutions to solve complex business problems. Collaborate with cross-functional teams to translate ambiguous problems into production-ready intelligent systems and mentor other data scientists.
The role involves identifying, curating, and preparing complex chemical datasets to integrate into machine learning algorithms. You will develop featurizations and apply traditional cheminformatics techniques to accelerate drug discovery.
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The Data Scientist will build predictive models and develop proprietary software tools to identify ore-forming processes and mineral deposits. They will collaborate with geoscientists to integrate complex geoscientific data and design field programs to reduce uncertainty in exploration targets.
The Data Scientist will build predictive models using scientific computing and statistical methods to locate ore-forming processes and predict mineralization in 2D and 3D, while helping to build a worldwide dataset with careful uncertainty quantification. They will create models and develop software to accelerate critical battery metal discovery, working closely with geoscientists to guide exploration and field programs.
The Data Scientist will build predictive models using scientific computing and statistical methods to locate evidence of ore-forming processes and predict mineralization locations in 2D and 3D. They will also help build a worldwide dataset, create models, and develop software to accelerate the discovery of critical battery metals.
The Staff Data Scientist will take deep ownership of high-impact problem spaces within advertising, specializing in measurement, identity, and signal quality, influencing strategic direction and setting a high technical bar. Key tasks include developing identity resolution models, advancing lift methodologies and experimentation, maximizing signal value for predictive performance, and defining ground truth evaluation frameworks.
Collaborate with data scientists and subject matter experts to build and optimize data pipelines for industrial AI and ML-Ops solutions. Ensure data integrity, cleanliness, and reliability while tracking performance metrics for 24/7 operational systems.
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