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Salary
$85k – $160k per year (Estimated)
Location
Remote (Canada)
Seniority
Senior · 2+ years exp
Employment
Full-Time
Overview
Company
Impact
Profile match
Jobgether is a Belgian recruitment platform built entirely around remote and flexible work, aggregating openings from thousands of employers that allow work from outside an office. Its matching engine ranks roles against a candidate's skills, seniority and stated preferences on location and flexibility, rather than leaving people to filter a keyword search, and it verifies how genuinely remote each posting is. The company also runs an AI screening layer that shortlists applicants for employers, and publishes research and guidance on distributed work practices alongside the job marketplace itself.

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Analyst, Analytics based in Canada.

This role offers the opportunity to turn complex data into actionable insights for a fast-paced B2B technology environment.

You will combine analytics, marketing measurement, AI, and data engineering to solve meaningful business and client challenges.

A key focus will be Generative Engine Optimization (GEO) and Answer Engine Optimization (AEO), helping organizations improve their visibility across AI-powered search platforms.

You will also contribute to data warehouse development, reporting automation, dashboards, experimentation, and technical projects.

The position blends hands-on technical delivery with client engagement, requiring you to communicate insights clearly to both technical and non-technical audiences.

You will collaborate across analytics, strategy, content, and technology teams while managing smaller client engagements and mentoring co-op students.

This is an ideal opportunity for an analytical, AI-curious professional who enjoys solving problems, building practical solutions, and turning data into measurable business impact.

Accountabilities

    • Lead GEO/AEO analyses to evaluate brand visibility, citations, and answer quality across AI search platforms, benchmark competitors, and translate findings into prioritized recommendations.
    • Analyze campaign, website, audience, and business performance data to identify trends, investigate drivers, answer strategic questions, and recommend actions.
    • Use LLMs and AI tools throughout daily analytical delivery, including research, data analysis, query development, workflow automation, and prompt optimization, while validating outputs against source data.
    • Contribute to the development of the internal data warehouse by gathering requirements, mapping source data, developing SQL transformations and reusable reporting tables, and validating results.
    • Integrate data from marketing platforms, CRM systems, and internal tools while supporting ingestion, refresh workflows, discrepancy resolution, and recurring reporting automation.
    • Establish consistent metrics and maintain clear documentation of data sources, transformations, assumptions, and data-quality controls.
    • Build and maintain dashboards, reports, presentations, and other analytical outputs that translate complex findings into clear recommendations for clients and internal stakeholders.
    • Design measurement plans and experiments, including repeatable GEO/AEO benchmarks, establish baselines, assess results, and clearly communicate limitations.
    • Manage small client engagements from kickoff through delivery, including defining objectives, planning activities, tracking scope and deadlines, leading status meetings, presenting recommendations, and escalating risks.
    • Supervise and mentor co-op students by providing onboarding, assignments, workload coordination, feedback, and quality oversight.
    • Deliver small technical projects from requirements through development, testing, documentation, and handoff, using Python and AI coding tools to create scripts, automations, integrations, prototypes, and internal tools.
    • Requirements

      • 2-4 years of experience in analytics, business intelligence, marketing measurement, or a related data-focused role; agency or consulting experience is an asset.
      • Strong practical experience using LLMs and AI tools, including prompt and context design, iterative workflows, output validation, and responsible handling of confidential information.
      • Advanced working knowledge of SQL and Excel for data cleaning, joining, transformation, and analysis, with familiarity with relational databases and data modeling.
      • Experience creating clear, useful dashboards using a business intelligence or visualization platform.
      • Familiarity with SEO, marketing measurement, AI search, and a strong interest in developing expertise in GEO/AEO; practical GEO/AEO experience is an asset.
      • Strong Python skills for data cleaning, analysis, automation, and API integrations, along with the ability to use AI coding tools to develop, test, debug, and maintain working solutions.
      • Experience with data pipelines, cloud data warehouses, or related data infrastructure is an asset, combined with strong judgment around data quality.
      • Ability to manage small client projects, coordinate contributors, present analytical findings clearly, and translate technical insights into practical business recommendations.
      • Experience mentoring, coaching, or reviewing the work of co-op students, interns, or junior colleagues.
      • Excellent written and verbal English communication skills and the ability to collaborate effectively across analytics, strategy, content, and technology teams.
      • B2B technology experience and French-language skills are considered assets.
      • Benefits

        • Fully remote, full-time position based in Canada.
        • Flexible work environment designed to support productivity and work-life balance.
        • Opportunity to work with major B2B technology clients and on innovative AI-driven marketing and analytics initiatives.
        • Hands-on exposure to GEO, AEO, LLMs, AI coding tools, data engineering, marketing analytics, and measurement strategy.
        • Opportunity to contribute to internal data infrastructure and develop practical technical solutions.
        • Collaborative environment spanning analytics, strategy, content, and technology disciplines.
        • Opportunities to manage client engagements and develop leadership and mentoring skills.
        • Professional growth opportunities within an innovative, technology-focused organization.
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