Software Developer - Data Science
Team: Engineering
Location: Canada
Workplace Type: remote
What You’ll Do
- Design and maintain robust ETL/ELT pipelines for large and complex datasets.
- Deploy and scale ML/OR models in Azure using Azure ML Studio, DevOps, and containerization.
- Build automated validation, monitoring, and benchmarking pipelines to ensure models are accurate, reliable, and robust.
- Collaborate closely with Data Scientists, Engineers, and Product teams to integrate AI solutions into core products.
- Own projects end-to-end, mentor peers, and help define best practices for code quality and model governance.
What You’ll Need
- Bachelor’s or Master’s degree in Computer Science, Software Engineering, Data Engineering, or related field.
- Strong programming skills in Python, plus experience with Java, C++, or similar languages.
- Solid understanding of data pipelines, APIs, and distributed systems.
- Hands-on experience with SQL/NoSQL databases and workflow orchestration tools (e.g., Airflow, Prefect, Luigi).
- Proven experience working with Azure services, including:
- Azure ML Studio, Azure Data Factory / Synapse, Azure Blob Storage, Data Lake, and Event Hub.
- Azure DevOps for CI/CD and infrastructure automation.
- Experience in ML model validation, evaluation, and monitoring.
- Strong knowledge of Git, CI/CD, automated testing, and code quality practices.
- Excellent problem-solving and collaboration skills.
Preferred Qualifications
- Experience with Azure Batch and Kubernetes for large-scale distributed workloads.
- Knowledge of data governance and security best practices in Azure.
- Prior work in optimization problems, transport/logistics, or large-scale ML systems.
- Exposure to DevOps/SRE practices for performance monitoring and reliability.
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