Hello, I am
Farid Adi Wijaya
Data & AI Specialist
Building Scalable Data Architectures for Finance
I specialize in designing robust data pipelines, data lakehouses, and predictive machine learning models. Bridging the gap between raw data and actionable financial intelligence with clean architecture and MLOps.
Core Tech Stack
Featured Architectures & Models
Highlighting scalable data pipelines, robust machine learning models, and efficient system architectures.
Single-Node Data Lakehouse
A robust conceptual data lakehouse built completely on a single node environment for high-speed small-to-medium data analytics processing.
Expected Credit Loss Predictor
A survival analysis model paired with an advanced XGBoost regressor for accurate ECL prediction compliant with IFRS 9 standards in the Finance sector.
Automated dbt Pipelines
High-performance data transformation workflows using dbt orchestrated as DAG blocks through Apache Airflow for a data warehouse setup.
Discussing data architectures or AI implementations?
Let's connect and build scalable systems for your next fintech product.
Data Snippets & MLOps Starters
Airflow + dbt Cosmos DAG
A dead-simple starter for orchestrating dbt with Airflow. Automates dbt run and test natively as Airflow TaskGroups.
XGBoost Credit Scoring Template
Starter kit for building Probability of Default models with built-in SHAP interpretations and CV pipelines.
Endorsements
"Farid transformed our raw, noisy data streams into a pristine lakehouse architecture. The impact on our ECL model accuracy and reporting speed was unprecedented."
Alex Chen
CTO at DefaultRisk Inc.
"A rare talent who understands both the rigid compliance needs of financial engineering and the bleeding edge of MLOps pipelines."
Sarah Jenkins
VP Engineering at NeoBank
"His open-source templates for dbt and Airflow cut our setup time by weeks. Invaluable contributions to the data engineering community."
David Park
Lead Data Scientist