Designed, cleaned, and maintained databases, including the freeBILy study database on schistosomiasis diagnosis and treatment in pregnant women and children in Madagascar. Consolidated longitudinal data from five follow-ups, integrating moment data, lab results, and new participant enrollments. Prepared summary reports, flagged and resolved non-conformities, and ensured compliance with study protocols. Developed automated scripts for reporting and data validation to streamline workflows and enhance accuracy during ongoing data entry. Conducted data preparation and statistical analyses to support study findings and reporting. Designed and managed REDCap projects for the team, optimizing data collection and management processes. Created educational materials and delivered training sessions in R programming, data management, and statistical methods for team members. Engaged in daily team activities, contributing to the success of ongoing projects and providing technical expertise in epidemiology and data management methodologies.Key Achievements: Successfully built and maintained a comprehensive database for a longitudinal study with complex follow-up requirements. Improved data quality and compliance through automated reporting and robust data validation procedures. Enhanced team capacity by providing hands-on training in advanced data management and programming techniques.

Hired as a Data Expert to assist on the development of a Results-Based Monitoring and Evaluation for a EU Project. I was responsible for:- Data analysis and data validation. - Evaluation of indicators and data collection methods. - Definition and construction of tools for data collection for each indicator (individual indicator sheets). - Definition and construction of tools for data aggregation (global indicator control sheet)- Definition of data presentation dashboard.Also, I've been helping researchers working with data and statistical methods and software.

Functions Performed:- Preparation of data for statistical analysis, portfolio analysis and risk analysis. Assistance in preparing analyses and visualizations for the regional team. Preparation of presentations for team training. - Preparation of Dashboards for periodic reporting and specific portfolios. - Review of pricing done by the actuarial team and local underwriting teams, which my academic background allows. Pricing done from scratch. Creation of raters for local use, along with preparation of material for training of local teams.- Portfolio Review and Analysis.- Literature reviews, especially epidemiological studies for the adequacy of policy coverages, under/over premium collection needs, adjustment of deductibles and risk analysis.- Work closely with local teams to assess their needs and respond accordingly. - Development of Data Governance solutions, and consequent awareness of process improvement and optimization. - Assisting in the systematization/automatization of processes through scripting.- Developed ILOE, Critical Illness, BTA and GPA pricing and raters.Part of the Early Career program. This program provides a platform for participants to launch or accelerate their careers. Through a range of approaches including innovative experiential learning and technical training, performance assessments, formalized mentoring, and exposure to senior leaders, the Early Career program offers unparalleled development opportunities for our diverse early career talent. The program is designed to evolve with the rapid pace of technological advancements.

I assisted the Mathematics Department of FCT Nova as a Multivariate Statistics Tutor for the 1st Semester of the 2022/2023 academic year, helping with lectures and preparing presentations and practical exercises.

Worked at the Non-Life Statistics and Technical Studies Calculate Division, my responsibilities were to calculate and monitor the technical provisions required to guarantee the organisation’s state of solvency, assessing their degree of prudence where applicable. Worked on the renewal process for the Auto Portfolio. Review and improvement of a Churn model, through feature engineering and overall model. performance enhancement. Estimation of a sensitivity curve to price variations by customer characteristics. Development of an optimization model as a function of the price sensitivity curve for churn minimization and revenue maximization, using genetic algorithms.

The RELIABLE project aims to develop a publicly accessible geographic dashboard with real-time and high spatial resolution information on health risks for building occupants during extreme weather events, heat waves and cold spells. The aim is to improve current alert systems by updating them, using advanced modeling techniques, such as ML methods, and drawing on new sources of public data. Furthermore, it is important that the new warning systems have a high spatial resolution in order to issue risk warnings more accurately and independently by area. In the elaboration of risk indicators, the intention is to use information from various data sources, which include an extensive historical record of mortality and morbidity indicators, as well as socio-demographic indicators that may be representative of the vulnerability of the population.In this project of a national dimension involving several institutions, INSARJ are responsible for carrying out a statistical analysis of all-cause mortality and hospitalisations in order to model the number of deaths and hospitalisations as a function of meteorological variables and to determine the conditions under which these variables have an impact on the population. Distributed Lag Non-Linear Models (DLNM) are at the forefront of the study of mortality and temperature associations, enabling the estimation of non-linear and lagged effects of temperature. It is also intended to develop simpler models with less complex interpretation, such as the DLM. Furthermore, modeling techniques like Time Series Regression Trees will be used and compared with modeling techniques already established in the literature for this type of associations. Finally, all models will culminate in the development of a risk warning indicator, active throughout the year, and easily understood by the entire population.Project Abstract accepted at the 34th Annual Conference of the International Society for Environmental Epidemiology 2022.

This research scholarship aims at introducing students, who have shown great interest and aptitude for the area of Operations Research, to a career in academic research. It was awarded by the Centro de Matemática Aplicações Fundamentais e Investigação Operacional to only 6 students from ISEG and FCUL. The work that was developed in the scope of the grant consisted in the development and implementation of scheduling models using as example a case of a Portuguese Call Center integrated in the health industry. The model implementation was done in Python with CPLEX packages for Python. This work resulted in a report that explains the reasoning behind the creation of the model and the results obtained.

Use Case: Social ListeningIn this project, within the scope of Data & Analytics, a research was made of what is already done in the area of Social Listening followed by an analysis of the metrics extracted from the social media pages of PwC Portugal in the various social networks where it is present. The analysis of the metrics was performed using Alteryx Designer. The results were subsequently presented using a set of Dashboards developed in PowerBI.