Software Engineer
23 hours ago
, Canada
Ateko, backed by Bell Canada
Full-time
Free with email or Google
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Free with email or Google
Master's or Ph.
D. in fields related to privacy-enhancing technologies, artificial intelligence, machine learning, cybersecurity, cryptography, computer science, data science, mathematics, or statistics. 5+ years of recent demonstrated Python development experience with libraries such as numpy, scipy, pandas, polars, pyspark, pytorch, scikit-learn, and matplotlib/seaborn. 3+ years of recent demonstrated extensive experience in DevOps principles, practices, and methodologies including SOLID principles, software version control, continuous integration and deployment for data science applications. Demonstrated experience analyzing and working with large, complex datasets within public sector, financial services, or similarly regulated environments. Demonstrated experience developing and implementing Privacy-Enhancing Technologies (PETs), including data anonymization, de-identification, differential privacy, secure multiparty computation, federated learning, homomorphic encryption, or similar privacy-preserving techniques. Demonstrated knowledge of data structures, data models, and data relationships, including structured, semi-structured, unstructured, nested, graph, and network-based datasets. Demonstrated experience using cloud-based data and analytics platforms, including Microsoft Azure, Microsoft Fabric, Azure Data Lake, Azure Databricks, Jupyter Notebooks, and Docker. #J-18808-Ljbffr
D. in fields related to privacy-enhancing technologies, artificial intelligence, machine learning, cybersecurity, cryptography, computer science, data science, mathematics, or statistics. 5+ years of recent demonstrated Python development experience with libraries such as numpy, scipy, pandas, polars, pyspark, pytorch, scikit-learn, and matplotlib/seaborn. 3+ years of recent demonstrated extensive experience in DevOps principles, practices, and methodologies including SOLID principles, software version control, continuous integration and deployment for data science applications. Demonstrated experience analyzing and working with large, complex datasets within public sector, financial services, or similarly regulated environments. Demonstrated experience developing and implementing Privacy-Enhancing Technologies (PETs), including data anonymization, de-identification, differential privacy, secure multiparty computation, federated learning, homomorphic encryption, or similar privacy-preserving techniques. Demonstrated knowledge of data structures, data models, and data relationships, including structured, semi-structured, unstructured, nested, graph, and network-based datasets. Demonstrated experience using cloud-based data and analytics platforms, including Microsoft Azure, Microsoft Fabric, Azure Data Lake, Azure Databricks, Jupyter Notebooks, and Docker. #J-18808-Ljbffr
