
Job Overview
Location
Toronto
Job Type
Full-time
Category
Data Science
Date Posted
June 21, 2026
Full Job Description
đź“‹ Description
- • Analyze marketing performance across paid, earned, and owned media campaigns, tracking full-funnel metrics from awareness to revenue
- • Partner with leadership to support strategic planning initiatives and establish performance targets for marketing initiatives
- • Manage ad hoc analytics requests and prepare comprehensive reports for weekly, monthly, quarterly, and annual business reviews, including executive and Board-level presentations
- • Optimize lead scoring models and attribution reporting through rigorous model validations to improve accuracy and alignment with revenue outcomes
- • Design and build interactive dashboards and reports using tools like Looker, BigQuery, and GA4 to deliver actionable insights and data-driven recommendations
- • Support Lead Flow and PipeGen reviews by creating detailed dashboards for closed-loop marketing reporting that connect campaign activity to pipeline and revenue
- • Enhance customer journey optimization through omni-channel campaign activation, A/B testing, and single-channel performance recommendations
- • Collaborate cross-functionally with Operations, Finance, Product, Engineering, Sales, and Marketing teams to align analytics initiatives with business goals
- • Translate complex data into clear, compelling business insights and recommendations using strong storytelling techniques
- • Present findings and strategic recommendations to executives and stakeholders at all organizational levels using Google Slides, PowerPoint, or similar tools
- • Maintain proficiency in key marketing platforms including Marketo, Salesforce, Segment, Hightouch, and paid/social media advertising platforms
- • Apply deep understanding of PLG (Product-Led Growth), SLG (Sales-Led Growth), and Closed Loop Marketing frameworks to guide performance analysis and optimization
- • Utilize advanced SQL and Python programming skills to automate data workflows, perform statistical analysis, and enhance reporting efficiency
- • Contribute to the continuous improvement of marketing analytics infrastructure and reporting standards in a hyper-growth B2B enterprise environment
🎯 Requirements
- • Bachelor's/Master’s degree in a technical field (e.g., Computer Science, Data Science, Statistics, Engineering, Mathematics)
- • 5+ years of deep analytics experience supporting GTM teams (Marketing and/or Sales) in hyper-growth B2B environments
- • Advanced SQL and Python programming skills; experience with AI tools for data analysis and automation
- • Platform Proficiency: Marketo, Salesforce, GA4, BigQuery, Looker, CDP (Segment, Hightouch); Paid and Social Media Platforms; certifications preferred
- • Cross-Functional Collaboration: Proven ability working with Operations, Finance, Product, Engineering, Sales, and Marketing teams
- • Communication Excellence: Strong storytelling abilities to translate complex data into clear business insights and recommendations
🏖️ Benefits
- • 3-month fixed-term contract engagement
- • Remote/hybrid work flexibility
- • Opportunity to work with a global AI leader at the forefront of enterprise AI innovation
- • Exposure to executive-level decision-making and Board-level reporting
- • Access to cutting-edge marketing analytics tools and infrastructure
- • Collaborative environment with cross-functional teams across Toronto, San Francisco, London, New York, Montreal, Seoul, Germany, and Paris
Skills & Technologies
See exactly how your profile matches this role — strengths, skill gaps, and what to do about them.
About Cohere Inc.
Cohere provides large language models and retrieval-augmented generation APIs for enterprise developers to embed conversational AI, search, summarization, and content generation into applications. Founded in 2021 by former Google Brain researchers, the company offers cloud and on-premise deployment, fine-tuning tools, and multilingual support to help organizations automate workflows, improve customer support, and analyze unstructured data while maintaining data privacy and security controls.
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