Alexander Trif

Data Scientist at Metegrity Inc. Machine Learning Pipelines & Production Analytics

Contact: Email: alextrif25@gmail.com LinkedIn: linkedin.com/in/alex-trif-972450185

Summary

Data Scientist focused on building end-to-end machine learning systems that turn messy, real-world data into reliable production solutions. Strong emphasis on automation, monitoring, and long-term maintainability across the full ML lifecycle.

Experience

Data Scientist — Metegrity Inc.

Design and maintain end-to-end machine learning pipelines, from data ingestion and feature engineering through model training and production deployment.
Build monitoring and validation systems to ensure model reliability over time.
Work with cross-functional teams to integrate predictive analytics into operational workflows, replacing manual processes with data-driven decision-making.
Conduct production readiness assessments and develop roadmaps for scaling ML systems.
Refactor and optimize analytical codebases to reduce complexity and improve maintainability.

Technical Skills

ML & Modeling: XGBoost, Scikit-learn, Random Forest, Logistic Regression, SVM, KNN, Decision Trees
MLOps: Model monitoring, drift detection, data validation, structured logging, scheduling, CI/CD
Languages: Python, R, SQL
Feature Engineering: Automated feature selection, data cleaning, pipeline development
Data Pipeline Development: End-to-end ingestion, transformation, and deployment workflows
Visualization & Reporting: Tableau, Power BI

Education

Post-Baccalaureate Diploma in Health Analytics — Okanagan College (2022–2024) Epidemiology, public health, biostatistics, health informatics, data management, and predictive modeling.
B.Sc. in Science, Major in Chemistry, Minor in Mathematics & Statistics — University of British Columbia Okanagan (2016–2019)

Key Skills

XGBoost

MLOps

R Programming

Feature Engineering

Data Pipeline Development

Languages

Fluent in English and Romanian, conversational in Spanish.