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Salary
$104k – $178k per year (Estimated)
Location
Remote (Canada)
Seniority
Senior · 5+ 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 Data Scientist based in Canada.

As a Senior Data Scientist, you will design and execute advanced analytical and machine learning solutions that address complex business challenges.

You will connect technical decisions with business objectives, helping teams turn data into meaningful and actionable insights.

The role combines hands-on expertise in machine learning, statistics, data engineering, and MLOps with strategic problem-solving.

You will work across cross-functional teams, communicate sophisticated concepts to non-technical stakeholders, and support high-quality decision-making.

A key part of the position is mentoring engineers and strengthening standards, best practices, and collaborative technical practices.

You will also contribute to the long-term evolution of data and ML platforms in a dynamic, international, and fully remote environment.

Accountabilities:

    The role focuses on building scalable, production-ready data science solutions while providing technical direction and mentorship across teams.

    • Design, develop, and scale advanced machine learning and deep learning models for production environments.
    • Apply statistical methods, experimental design, and causal inference to solve complex analytical problems.
    • Conduct and manage ML experimentation using tools such as MLflow, Weights & Biases, and Databricks ML.
    • Develop efficient data workflows and perform large-scale data manipulation using advanced SQL.
    • Leverage big-data technologies such as Spark and Databricks to optimize model training and scoring.
    • Implement and improve MLOps workflows covering model registries, deployment, monitoring, drift management, and retraining.
    • Work with cloud-based machine learning platforms such as Azure ML, Amazon SageMaker, or Google Vertex AI.
    • Evaluate technical trade-offs and make sound architecture and implementation decisions.
    • Translate complex technical concepts and analytical findings into clear recommendations for non-technical and executive audiences.
    • Develop compelling data visualizations and storytelling approaches tailored to business and leadership needs.
    • Mentor junior and mid-level engineers, promote technical excellence, and establish strong engineering practices.
    • Break down ambiguous business and technical challenges into actionable, executable solutions.
    • Take ownership of issues and proactively contribute to the long-term evolution and scalability of data platforms.
    • Collaborate with cross-functional teams to improve decision-making, solution quality, and technical standards.
    • Requirements:

      The ideal candidate combines strong technical depth in data science and machine learning with strategic thinking, communication skills, and the ability to mentor others.

      • Degree in Mathematics, Computer Science, Machine Learning, or a related technical field.
      • At least 5 years of professional experience in data science, with a proven track record of building and architecting production-level data solutions.
      • Advanced Python skills for machine learning and deep learning, including NumPy, pandas, scikit-learn, and PyTorch or TensorFlow.
      • Strong knowledge of statistics, experimental design, and causal inference.
      • Proven experience developing and scaling complex ML/DL models for production use.
      • Experience with ML experimentation and tracking platforms such as MLflow, W&B, or Databricks ML.
      • Advanced SQL skills for large-scale data manipulation and analytical workloads.
      • Strong understanding of MLOps principles, including deployment, monitoring, model drift, registries, and retraining.
      • Experience with Spark, Databricks, or other big-data platforms.
      • Hands-on experience with cloud ML platforms such as Azure ML, SageMaker, or Vertex AI.
      • Strong data visualization and storytelling capabilities, particularly for executive-level audiences.
      • Ability to assess technical trade-offs and clearly communicate technical decisions.
      • Strong communication skills with the ability to explain complex concepts to non-technical stakeholders.
      • Proven mentoring abilities and a commitment to technical standards and best practices.
      • Strong problem-solving skills and the ability to turn ambiguous challenges into structured solutions.
      • Ownership mindset, proactive approach, and interest in long-term platform evolution.
      • English proficiency at a minimum B2 level.
      • Benefits:

        • 100% remote work, providing flexibility to work from the location where you are most productive.
        • International career opportunities with exposure to projects and teams across multiple countries.
        • Professional growth within a dynamic, collaborative, and technology-focused environment.
        • Opportunities to work on advanced Cloud, Cybersecurity, Data, and software development projects.
        • Health insurance.
        • Life insurance.
        • Tech Visa support for eligible employees located outside the European Union.
        • Exposure to international projects across Europe and other global markets.
        • Opportunities to collaborate with diverse, cross-functional teams and develop your technical expertise.
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