Open to opportunities

arold User

@michelsimo

Data Scientist translating business problems into data-driven solutions, delivering high-performing, interpretable models with real-world impact.

Canada

Message

What I'm looking for

I seek roles where I can build and productionize ML models, collaborate with engineering teams, and drive measurable business impact in hybrid or remote settings.

Data Scientist with 9+ years of experience delivering measurable business impact across end-to-end machine learning lifecycles, from problem formulation and feature engineering to model development and production deployment. Strong foundation in traditional machine learning, statistical modeling, and analytics, complemented by hands-on experience with Generative AI systems, including Retrieval-Augmented Generation (RAG), embeddings, and LLM evaluation frameworks. Proven ability to translate complex business and operational challenges into scalable, production-ready solutions, build reliable data and feature pipelines, and partner effectively with engineering and business stakeholders to drive adoption, performance, and sustained outcomes.

Experience

Work history, roles, and key accomplishments

Current

Data Scientist

Current

NovaAnalytics, Inc.

Jun 2024 - Present (1 year 8 months)

Built end-to-end classification and regression pipelines that improved lead quality scoring by 18% and reduced manual review time by 30%; implemented MLflow tracking and model monitoring to reduce deployment issues. Optimized ETL with Airflow and Spark, cutting model training time by 25% and introduced a RAG proof-of-concept using embeddings and Pinecone for semantic retrieval.

Python scikit learn MLFlow Airflow Spark Pinecone Embeddings Model Monitoring

Data Scientist

BlueSky Retail Labs

Jul 2022 - May 2024 (1 year 10 months)

Developed time series forecasting models that improved forecast accuracy by 12% and reduced stockouts; deployed anomaly detection reducing false positives by 22% and built dashboards that cut reporting latency from days to hours. Led A/B testing and productionized models using Docker and CI/CD to improve deployment reliability.