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Salary
$94k – $160k per year
Location
Remote (Canada)
Seniority
Staff · 6+ 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 Manager, Data Science based in Canada.

As a Manager, Data Science, you will lead the delivery of advanced analytics, statistical modeling, data pipelines, and AI-powered decision-support solutions.

You will combine hands-on technical execution with client engagement, translating complex business challenges into practical analytical solutions.

The role spans machine learning, generative AI, data engineering, visualization, and production analytics within a collaborative distributed environment.

You will work closely with client stakeholders and onsite and offshore teams to define requirements, deliver solutions, and ensure successful implementation.

Your work will directly support commercial decision-making through reliable models, reporting, experimentation, and actionable insights.

You will also contribute to technical quality, automation, documentation, and the development of junior team members.

This is an ideal opportunity for an experienced data science professional who enjoys solving complex problems while remaining close to both the technology and the business.

Accountabilities

    • Translate client and stakeholder needs into clear analytical requirements, objectives, success metrics, and actionable data solutions.
    • Build, maintain, and improve statistical, predictive, sales attribution, conversion, and machine learning models across multiple business areas.
    • Design and implement generative AI solutions, including LLM applications, vector search, embedding-based retrieval, and agentic automation.
    • Support AI-powered workflow agents in production by implementing reliability measures such as event logging, monitoring, and recovery mechanisms.
    • Conduct exploratory data analysis, statistical testing, model comparisons, and documented evaluations to support sound analytical decisions.
    • Develop efficient SQL queries and Python-based data transformation workflows using cloud data platforms, particularly BigQuery.
    • Validate and reconcile pricing, transaction, and performance data against source systems, identifying discrepancies and ensuring reporting accuracy.
    • Build and maintain dashboards, reporting views, and lightweight analytical applications using Tableau, JavaScript, and Google Apps Script.
    • Maintain data pipelines, data architecture, and cloud infrastructure supporting ad hoc analysis and recurring reporting requirements.
    • Develop sales attribution and conversion methodologies, including analysis of channel overlap and contribution.
    • Perform product- and transaction-level analysis, including inventory matching, conversion performance, pricing accuracy, and SLA-related metrics.
    • Conduct code reviews, quality assurance, and audit activities to maintain high standards of analytical and reporting accuracy.
    • Collaborate effectively across distributed onsite and offshore teams, ensuring clear technical handoffs and consistent delivery.
    • Mentor junior team members, share technical knowledge, and contribute to documentation, automation, and standardized QA practices.
    • Communicate analytical findings and complex quantitative concepts clearly to non-technical stakeholders and business leaders.
    • Requirements

      • Bachelor's or Master's degree in Data Science, Computer Science, Mathematics, Statistics, Business Analytics, or a related quantitative discipline.
      • 6-8 years of professional experience in advanced analytics, data science, machine learning, or a related field.
      • Demonstrated experience owning and delivering production data science or analytical models, including client-facing projects.
      • Expert-level proficiency in SQL and Python, with working knowledge of JavaScript and Google Apps Script.
      • Advanced experience with Google Cloud Platform, particularly BigQuery, data architecture, and data warehousing.
      • Strong knowledge of statistical modeling, significance testing, exploratory data analysis, predictive analytics, and experimental methodologies.
      • Practical experience with Tableau and the development of custom dashboards or lightweight web-based analytical tools.
      • Familiarity with LLM-based applications, vector databases, retrieval systems, and agentic AI development practices.
      • Ability to translate ambiguous stakeholder requests into structured analytical requirements, technical solutions, and measurable outcomes.
      • Strong understanding of commercial analytics, including conversion rates, pricing, inventory accuracy, performance measurement, and SLA metrics.
      • Excellent communication skills, with the ability to explain complex technical and quantitative concepts to non-technical audiences.
      • Ability to work effectively in distributed onsite/offshore team structures and manage priorities independently.
      • Strong problem-solving, analytical thinking, documentation, and quality-assurance skills.
      • Experience mentoring colleagues or contributing to team development and knowledge-sharing initiatives.
      • Comfortable balancing hands-on coding and modeling responsibilities with client communication and project leadership.
      • Benefits

        • Competitive annual salary range of $94,000-$160,000, depending on experience, knowledge, skills, and other relevant factors.
        • Remote work opportunity for candidates based in Canada.
        • Flexible working approach designed to support collaboration and productivity.
        • Medical, vision, and dental insurance.
        • Life insurance coverage.
        • Short-term and long-term disability insurance.
        • 401(k) retirement plan.
        • Flexible paid time off.
        • At least 15 paid holidays per year.
        • Paid sick and safe leave.
        • Paid parental leave.
        • Opportunities to work on advanced analytics, machine learning, generative AI, and data-driven business solutions.
        • Collaborative environment with exposure to distributed, cross-functional, and international teams.
        • Opportunities for professional growth, technical development, mentoring, and knowledge sharing.
        • Commitment to equal opportunity, inclusion, and reasonable workplace accommodations.
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