Sami Rodrigue Email & Phone Number

Toronto, On, Ca

Developed and maintained robust data retrieval and analytics microservices utilizing FastAPI and NestJS/Node.js.Spearheaded the integration of the Strategy and Factory design patterns to modularize metrics in the anomaly detection service, enabling dynamic runtime adjustments and enhancing system adaptability.Engineered a user-friendly dropdown selection feature using the MUI package, streamlining metric toggling in the anomaly detection service, which improved user engagement and demonstrated runtime configuration.Implemented Redis queues to horizontally scale anomaly detection services, separating data validation from calculation, improving system scalability.

Built Machine Learning pipelines for companies spanning diverse industries such as Mining, Finance, and E-commerce:* Implemented NLP models for categorizing the websites of private companies for a fintech company.* Built a data pipeline using Azure Data Factory and Azure Functions to categorize unlabeled car features by applying rules derived from LDA.* Utilized Autoencoder and CNN deep learning techniques within Docker containers to forecast safety scores for subsections of a gold mine.Developed and optimized an ETL pipeline for a media conglomerate, transforming DVR log data into actionable viewership insights for targeted advertising using AWS.Utilized orchestration tools such as Azure Logic Apps and Data Factory to integrate internally developed ETL scripts along with custom functionalities in Azure Functions in Python for a lift and shift of a data ingestion pipeline of a luxury hotel chain.

Collaborated with the Communication Research Center (CRC), to combine DSL’s expertise in machine learning with CRC’s domain knowledge in telecommunication to achieve real time intelligence for spectrum usage.Led the team in the implementation of Hidden Markov Models and Neural Networks in Python to predict channel occupancy using signal and weather data. Designed experiments to identify the combination of hyperparameters that minimized the error for the models.Gave biweekly presentations to CRC’s managers and researchers on novel research in telecommunication and findings on exploratory data analysis of CRC’s dataset.

Worked as a TA for the CIND 123 Data Analytics: Basic Methods course which comprised of introduction to R and statistics.Prepared lab questions to teach the inner workings of the R programming language and engaged with students in labs to explore applications of statistics using R.

Aggregated data from source systems and spreadsheets using a business managed application. Normalized and validated the generated data to produce periodical client profitability reports. Conducted ad-hoc analyses on historical reports to investigate the source of lending revenues that are used to identify the accurate allocation of these revenues to the relevant product managers.

Master Of Science - Ms, Data Science And Analytics

Bachelor’S Degree, Business/Commerce, General

Computer Science

Completed COMP 378: Introduction to Databases.

Open Learning, Computer Science

Completed courses: - COMP 2231: Data Structures, Algorithm Analysis, and Program Design - COMP 3051: Algorithm Design and Analysis