Division: Data Science & IT Architecture
Work Status: Full-Time
Location: Toronto, ON (Hybrid)
About the Role:
We are seeking a Data Science Software Developer who sits at the intersection of software engineering and applied data science. This role is responsible for building robust, scalable data products and tools that enable advanced analytics, machine learning, and decision support across Corus.
You will work closely with data scientists, analysts, and business stakeholders to produce models, automate workflows, and build data-driven applications.
You will contribute by:
- Design, develop, and maintain data-centric applications and services supporting analytics and AI use cases
- Software design and architecture for addressing individual business problems
- Build and optimize ETL/ELT pipelines in cloud environments (GCP preferred)
- Productionize data science models into reliable, scalable software solutions
- Develop APIs and backend services to expose data and model outputs
- Collaborate with the Data Science team to translate prototypes into production systems
- Deploy and manage machine learning models using MLOps best practices
- Implement monitoring, logging, and observability for data pipelines and services
- Ensure data quality, performance, and system reliability aligned with SLAs/SLOs
- Contribute to DevOps practices including CI/CD, testing, and infrastructure-as-code
Skills and experience you will bring:
- BA/BS degree in Computer Science/Computer Programming or related field along with 5+ years of experience in software development, with exposure to data platforms
- Strong proficiency in Python (primary) and SQL
- Experience with data processing frameworks (e.g., Spark, Pandas, Apache Beam)
- Experience building and maintaining data pipelines (Airflow, Cloud Composer, etc.)
- Hands-on experience with cloud platforms (GCP preferred: BigQuery, Cloud Run, GCS)
- Familiarity with REST APIs and microservices architecture
- Experience with version control (Git) and CI/CD pipelines
- Great communication skills with the ability to translate technical speak to non-technical audiences
Nice-to-Have
- Exposure to machine learning workflows and model deployment
- Experience with Looker, Dataform, and BI tools
- Familiarity with data governance and data quality frameworks
Application Deadline: July 1, 2026
