Academy Accreditation - AI Agent Fundamentals

Master of Science - MS

- Develop end-to-end data solutions on the Databricks platform, collaborating with cross-functional
teams to identify business requirements and implement scalable solutions.
- Development of a Market Basket for recommending promotions with a high probability of success for the traditional channel

Business Intelligence Specialist

- Implementation of Survival Analysis to find the optimal number of calls to ensure customer retention above 80%.
- Development of a churn model with clients that had a downward sales trend in the last 6 months with xgboost.
- Implementation of Data Governance through the concentration of customer information with sales KPIs in the master database with an Azure architecture.
- Forecast of the number of clients

Data Analyst

- Development and deployment of machine learning risk models for predictive analytics using GB, leveraging Databricks MLflow and other relevant tools

- Feature engineering with Spark to upgrade machine learning model's performance

- Create efficient MLops pipelines using Python, Spark, and SQL, ensuring data quality and integrity
throughout the entire process

- Development of a framework for monitoring machine learning models using important metrics such as KS distance and population stability.

Data Scientist

-Built a production-grade MLflow-based MLOps framework for model lifecycle management, enabling automated experiment tracking, model versioning, drift detection, performance monitoring (Gini, and continuous validation of deployed models.
- Update XGBoost risk models for auto and commercial insurance portfolios within a Spark-based scalable analytics platform.

Conducted computational neuroscience research on neuronal reliability under stochastic synaptic inputs using conductance-based dynamical models.

 Developed numerical simulations and parameter-space analyses to quantify reliability measures and spike-train responses in biologically inspired neuron models.

Research assistant of Dr. Alessio Franci

<p>- Developed Azure Databricks and Azure Data Factory pipelines integrating SAP invoice, credit note, payment, and order data, supporting the processing of millions of transactional records
- Reduced end-to-end batch processing times from several hours to less than 30 minutes, through Delta Lake optimization, partitioning strategies, and PySpark performance tuning.</p>

Data Engineer (AB InBev Project)

Data Science| MLOps | MS in Mathematical Modelling

Know about Pamela Puigvert Angulo's work experience, education, bootcamps, certifications, and much more. Pamela Puigvert Angulo