• Create ETL workflows to fetch data from external sources and channel it to applications and stakeholders.• Monitor the completeness and quality of the data to proactively adapt to changes in data sources.• Port feeds from older frameworks / technology stacks into the latest standards.• Develop tools and frameworks to improve the creation and maintenance of data feeds.• Support users across Vitol’s offices worldwide.

• Develop and maintain a Python backend that performs complex calculations as part of an Integrated Production Surveillance and Optimization system.• Build and maintain APIs for backend based modular services (FastAPI, Pydantic, Starlette).• Utilize Pandas/Numpy to work with analytics services across the team.• Use SQLAlchemy to interact with a SQLServer database, and alembic for schema version control.• Process data asynchronously with asyncio and multithreading, using custom job queues as well as Celery.• Leverage Docker, Kubernetes and Helm to containerize and deploy applications.• Communicate with Product Owner and SME to translate complex real world needs into clear requirements.• Use Azure Cloud as well as Terraform/Terragrunt to configure and interact with the cloud infrastructure used by the services (e.g.: Service Bus queues, Redis, AKS, etc).

• Originally hired as an analyst; from day 1, leveraged programming skills to improve internal firm processes and create advanced analyses for our clients. Transitioned to a full-time Python developer after 12 months.• Entrusted with creating and conducting a training seminar in Python skills for my colleagues, including consultants up to 10 years my seniors.• Used Pandas, Numpy, Statsmodels to create sales / logistics forecasting and planning tools for our clients.• Utilized Qt, PyQt5 and QtCreator to create simple GUIs, and fbs / NSIS to package the apps into installers.• Created SQLite and PostgreSQL databases with automatically triggering PL/SQL scripts and accessed them from Python using sqlite and psycopg.• Scraped many different data sources using Scrapy, BeautifulSoup / requests, and Selenium; communicated with various APIs to extract information / conduct analyses (e.g.: Bing Maps API).• Simulated a complex system through Object-Oriented modeling and optimized it using machine learning and heuristic algorithms. No machine learning library was used for this, since the methods required for simulated annealing were built into the custom object models.• Exported analysis results to Excel spreadsheets using openpyxl and created data-driven Powerpoint presentations using python-pptx.• Participated in the solution of business problems in the Manufacturing and Retail sectors, regarding commercial strategy, capability development, inventory management and corporate governance.

Taught Econometrics and advanced statistics to Econ and Finance majors.

• Automated time-consuming data extractions from PDFs as part of a due-diligence process (Py2PDF / regex).• Worked on 5 investment opportunities and 6 live deals and created valuations using industry comparables, precedent transactions, discounted cashflows, and Monte Carlo simulations; performed market research and data analysis for the Management Board; worked with LOIs, term sheets and contracts.

Gave lectures and workshops for exams similar to the GMAT, significantly boosting the acceptance rate for IPADE’s full-time master’s program (MEDE).

Researched potential targets for our clients and elaborated reports to present M&A opportunities; gathered and processed company information and market data to analyze our targets’ business economics; calculated WACCs for 2 live deals.