Machine Learning Engineer - Express Scripts Canada
$115,000–$125,000 year
HybridMississauga, Ontario, Canada
Job Summary
Design and implement ML data pipelines to ingest, engineer, and persist features from Oracle, including robust logging and environment-based configuration. Build and validate unsupervised ML models using dimensionality reduction techniques, leveraging chunked processing for large datasets. Serve models as REST APIs with health endpoints and structured response models, while instrumenting application logs and operational run scripts. Orchestrate end-to-end validation workflows, writing curated results back to Oracle tables and maintaining required schemas. Collaborate with business teams to interpret clusters and incorporate feedback loops into subsequent runs. Support deployment workflows in sandboxed environments and participate in CI/CD pipelines for model operationalization. Ensure performance, quality, and responsiveness of data pipelines and APIs while maintaining code quality and automation.
Required Qualifications
- 5+ years application development experience
- 3–5 years of professional experience in data science / machine learning engineering with Python, including productionizing data pipelines or ML services
- Bachelor's degree in Computer Science, Data Science, Engineering, Mathematics, or a related field (or equivalent practical experience)
- Strong with NumPy, pandas, scikit-learn, SciPy (sparse), joblib, CLI (argparse), and data visualization (matplotlib/seaborn)
- Practical experience with MiniBatchKMeans/KMeans, DBSCAN, TruncatedSVD/PCA, cluster evaluation (silhouette, CH, DB), and stability/bootstrapping
- Writing performant SQL; using SQLAlchemy and oracledb for reads/writes; creating tables/DDL; batch inserts; column/type normalization
- Feature engineering over large volumes with chunked processing, environment-aware configs (.env), robust logging, and CSV/DB outputs
- Batch prediction flows via REST (e.g., httpx client) and schema-compatible exports
- Proficient with Git; familiarity with Jenkins/OpenShift pipelines and on-prem deployment constraints
- Experience in Healthcare domain with exposure to Fraud, Waste, and Abuse detection in pharmacy/claims, risk scoring thresholds, and audit support artifacts
- Experience with on-prem, masked datasets and familiarity with Docker/OpenShift deployment patterns for ML APIs
- Enhanced Reliability Clearance from the Federal Government
Desired Qualifications
- Experience with AI pipelines including data preprocessing, feature extractions, model training, and evaluation
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