Barcelona, Catalonia, Spain
• Led data science projects for an e-commerce platform to improve ranking, recommendations and ad placement. • Led genAI projects to enhance the search page using proprietary and fine-tuned open-source models. • Developed simulation frameworks to evaluate and validate proposed solutions prior to production implementation. • Identified and developed new data science opportunities to address business challenges. • Mentored team members on data science, engineering practices, and project development. • Key technologies: Python (Pandas, NumPy, Scikit-learn, Unsloth, Transformers, LangChain), SQL, Google Cloud Platform (BigQuery, Vertex AI), Looker Studio, Streamlit.
• Developed forecasting solutions for demand planning. • Led the end-to-end deployment and execution of the forecasting solution, designing the data pipeline with Azure Data Factory (ADF) and prioritizing new feature integration. • Designed and implemented models for forecast decomposition to provide insights into demand drivers. • Designed and built core modules for a forecasting engine. • Established CI/CD pipelines for automated testing and deployment of machine learning models. • Key Technologies: Python (Pandas, NumPy, Matplotlib, Scikit-learn, Statsmodels), Spark, Azure (including Azure Data Factory), Databricks and MS Power BI.
• Worked on the risk team managing split payment products. • Developed and implemented machine learning-based risk models to optimize the automated decision engine. • Built time-series forecasting models to predict credit losses. • Engineered and integrated new features into a Redshift data warehouse for modeling and analysis using dbt. • Performed risk assessments, monitored key performance indicators (KPIs), and conducted data analysis to inform improvements. • Key Technologies: Python (Pandas, NumPy, Matplotlib, Scikit-learn, CatBoost), R (Tidyverse, glmnet), SQL, AWS (Redshift, Sagemaker), dbt and Tableau.
• Worked on data analytics projects and contributed to open data initiatives. • Designed and developed custom data visualization dashboards. • Key Technologies: Python (Pandas, NumPy, Matplotlib, Scikit-learn, Plotly, Django).
• Provided technical support to BIOCENIT group members. • Applied machine learning techniques to projects in urban science and data visualization. • Administered an on-premise computing cluster. • Key Technologies: Python (Pandas, NumPy, Scikit-learn, Plotly), Keras, Spark, Dask, Django, SQL.