Senior Data Scientist

Job Description

Job Title: Senior Data Scientist

Location: Toronto

Department: AI & Data Engineering

Type: Full-time

Reports to: Head of Applied AI & Data Engineering

Who is EnStream

EnStream is a leader in secure digital identity and mobile data intelligence, working to advance the future of digital trust in Canada. We build innovative data-driven models that enhance the integrity, reliability, and safety of digital identity ecosystems. Our latest initiative leverages advanced data science, machine learning, and deep learning to further grow and sustain digital trust across Canada.

Our mission is to empower frictionless trust in every interaction. EnStream is dedicated to increasing trust and convenience for Canadians using real-life, verified identities and network data held by trusted telco networks. At EnStream, every team member plays a critical role in shaping our strategy and delivering meaningful impact across industries.

About the Role

We are seeking a Senior Data Scientist to join EnStream's Data & AI team and help design and build models that measure behavioural, relational and contextual integrity across the EnStream ecosystem. You will apply your expertise in data wrangling, feature engineering, machine learning, and deep learning-with a strong preference for experience in graph-based and semi-supervised learning-to develop models that are explainable, scalable, and production-ready. Additionally, you will conduct ad-hoc statistical analysis to support production operations and future initiatives.

What You'll Do

• Research, design, and prototype Machine Learning/Deep Learning models for identity trust and integrity scoring
• Prepare, clean, and engineer features from large, complex telecommunications and fraud datasets
• Develop and evaluate unsupervised and semi-supervised learning models (including graph-based techniques)
• Collaborate with data and application engineering teams to operationalize data engineer pipeline and AI/ML models
• Support ad-hoc statistical analysis, data visualization, and insight generation for exploratory studies and impact assessments
• Contribute to the design of model monitoring, explainability, and drift detection frameworks
• Participate in peer reviews, documentation, and knowledge sharing within the Data & AI team

What You Bring

Must-Have Skills & Experience

• Bachelor's or higher degree in Computer Science, Data Science, Engineering, Mathematics, or related field
• Domain knowledge in fraud detection
• 5+ years of hands-on experience in Data Science, Machine Learning, Deep Learning
• Proficiency in Python (e.g. numpy, pandas, PySpark, scikit-learn, PyTorch/TensorFlow, matplotlib, seaborn), SQL, hyperparameter optimization framework (e.g., Ray Tune, Optuna, Hyperopt), and graph ML frameworks (e.g., PyTorch Geometric, NetworkX)

What Sets You Apart

• Domain knowledge in digital identity and telecommunications
• Experience with advanced Unsupervised and Semi-Supervised Learning techniques
• Experience in Data Engineering or ML Engineering
• Experience with AWS S3, SageMaker, and lakehouse architecture
• Experience implementing model monitoring, data/concept drift detection and explainability frameworks (e.g. SHAP, LIME)

Why Join Us?

• Contribute to a national-scale initiative defining the future of digital trust in Canada
• Work on cutting-edge graph-based semi-supervised learning applications using real-world identity data
• Collaborate with a highly skilled, cross-functional team