Recommended expert
Geraldine Castillo
Solution Engineer (Data & ML Integration)
Experience
May 2025 - Present
9 monthsErding, Germany
Solution Engineer (Data & ML Integration)
Amadeus Data Processing GmbH
- Designed ML-ready data integration workflows between on-premise systems and cloud platforms (Snowflake, AWS Redshift, Azure), enabling scalable feature engineering and model deployment
- Implemented automated ML pipeline deployment using Python, SQL, and CI/CD tools, reducing model deployment time by 60%
- Developed data transformation logic for master data synchronization across ERP and analytics systems, ensuring data quality for predictive models
- Collaborated with cross-functional teams to translate business requirements into mathematical specifications for ML solutions
Jul 2024 - Feb 2025
8 monthsPhilippines
Senior Data Scientist & ML Engineer
IQ-EQ Global Investor Services
- Developed and validated predictive models for customer segmentation and revenue forecasting using ensemble methods (XGBoost, Random Forest), achieving 85% accuracy
- Applied advanced statistical modeling techniques (Bayesian inference, multivariate regression) to optimize pricing strategies, contributing to 12% revenue growth
- Operationalized ML models on Azure ML platform with automated retraining pipelines and monitoring dashboards
- Integrated ERP data with cloud analytics platforms, processing complex distributed data sources for feature generation
- Conducted hyperparameter tuning and cross-validation for model optimization, improving F1-score by 18%
Dec 2022 - Jul 2024
1 year 8 monthsPhilippines
Data Scientist & ML Specialist
Ernst and Young (EY)
- Developed production-ready ML models using TensorFlow and PyTorch for customer churn prediction, achieving 89% recall and reducing churn by 15%
- Applied semi-supervised learning techniques to leverage unlabeled data, improving model performance by 22% with limited labeled samples
- Implemented time series forecasting models (Prophet, ARIMA, LSTM) for demand prediction, achieving MAE improvement of 35% over baseline
- Designed and deployed scalable ML infrastructure on Snowflake + AWS, processing 10M+ customer interactions daily
- Performed advanced feature engineering including lag features, rolling statistics, and interaction terms, creating 50+ features from raw data
- Translated complex business optimization problems (budget allocation, campaign ROI) into mathematical formulations and implemented solutions
- Processed semi-structured data (JSON, logs) from multiple sources using PySpark for distributed processing and model training
Feb 2020 - Dec 2022
2 years 11 monthsPhilippines
Machine Learning Engineer
Infor
- Built and operationalized gradient boosting models (XGBoost, LightGBM) for customer lifetime value prediction, contributing to 10% revenue growth
- Developed end-to-end ML pipelines on AWS (SageMaker, S3) and Snowflake, including data preprocessing, model training, and automated deployment
- Applied ensemble learning methods combining multiple models to achieve 92% accuracy in fraud detection, reducing false positives by 40%
- Implemented A/B testing framework for model evaluation, measuring statistical significance and business impact of ML interventions
- Performed data wrangling on complex, distributed data sources (ERP, e-commerce, CRM) using Python and SQL
- Optimized hyperparameters using grid search and Bayesian optimization, reducing model training time by 50% while improving performance
Jan 2019 - Jan 2020
1 year 1 monthPhilippines
Data Scientist
Ecorenew Group
- Developed time series forecasting models using ARIMA and Prophet, improving demand prediction accuracy by 25% for inventory optimization
- Built pricing optimization engine using regression models and constraint optimization, improving gross profitability by 10%
- Applied statistical analysis and hypothesis testing to identify revenue drivers and operational bottlenecks
- Integrated e-commerce data with analytics systems for real-time sales and product performance tracking
Summary
Data Scientist with 5+ years of experience developing and operationalizing machine learning models to solve complex business problems. Expertise in statistical modeling, deep learning, and cloud-based ML platforms (AWS, Azure, GCP). Proven track record in translating business requirements into mathematical optimization problems and deploying production-ready ML solutions. Specialized in feature engineering, ensemble methods, and Foundation Models (LLMs) integration. Published researcher in AI applications with strong foundation in Python, TensorFlow, and distributed ML systems.
Skills
- Machine Learning & Deep Learning: Xgboost, Random Forest, Gradient Boosting, Neural Networks, Tensorflow, Pytorch, Ensemble Learning
- Statistical Modeling: Bayesian Inference, Multivariate Statistics, Time Series Analysis, Hypothesis Testing, A/b Testing
- Advanced Ml Algorithms: Semi-supervised Learning, Reinforcement Learning, Causal Inference, Synthetic Data Generation
- Cloud Ml Platforms: Aws (Sagemaker, S3, Redshift), Microsoft Azure (Ml Studio, Data Lake), Google Cloud (Vertex Ai, Bigquery)
- Ml Operations & Deployment: Model Versioning, Hyperparameter Tuning, Cross-validation, Ci/cd For Ml, Apache Airflow
- Programming & Tools: Python (Pandas, Numpy, Scikit-learn), R, Pyspark, Sql, Dbt, Git
- Foundation Models & Genai: Llm Integration, Transformer Models, Fine-tuning, Prompt Engineering, Rag Architecture
- Data Engineering: Complex Data Wrangling, Distributed Data Processing, Feature Engineering, Data Pipelines
Languages
Tagalog
NativeEnglish
AdvancedGerman
ElementaryEducation
Mar 2025 - Aug 2026
Technische Hochschule Deggendorf
M.Eng. · Applied AI for Digital Production Management · Deggendorf, Germany
Feb 2021 - Feb 2025
Mapua University
M.Sc., Specialization: Advanced Machine Learning, Statistical Modeling, Deep Learning, Time Series Analysis · Business Analytics · Philippines · 1.3 - Excellent
Jun 2010 - Apr 2015
Polytechnic University of the Philippines
B.Sc. · Industrial Engineering · Philippines · 1.9 - Very Good
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