Diogenes Silva Pedro Kit chener

Full Stack Developer at Mindsight

Developed features for HR platforms used by 600+ companies, building full-stack solutions with Django, React, PostgreSQL, and Docker. Collaborated with Product, Design, and Customer Success teams to deliver improvements in operational efficiency and customer autonomy. Resolved a critical production issue affecting misleading survey analytics. Built a self-service survey creation platform that reduced customer success workload by 65% and survey setup time from 80 to 15 minutes. Implemented automated survey analytics dashboards, replacing manual reporting that took ~20 minutes per client and enabling real-time insights for clients and internal stakeholders.

Full Stack Developer at Mind s i g h t

Developed features for HR platforms used by 600+ companies. Architected and implemented full-stack solutions using Django, React, PostgreSQL, and Docker to support scalability, maintainability, and reliability across critical HR workflows. Partnered with Product, Design, and Customer Success to deliver improvements in operational efficiency and client autonomy. Resolved a production issue that caused misleading survey analytics and improved data accuracy for better decision-making. Built a self-service survey creation platform enabling clients to configure and launch surveys independently, reducing Customer Success workload by 65% and cutting setup time from 80 to 15 minutes (81% improvement). Created an automated survey analytics dashboard replacing manual reporting that took ~20 minutes per client, eliminating recurring maintenance and providing near real-time insights.

Teaching Assistant, Data Visualization (Data Science MBA Program) at University of Sã o Paulo

Provided technical support and tutoring for 100+ graduate-level students, assisting with theory and application of modern data visualization principles.

Undergraduate Research Project - Network Visualization at University of Sã o Paulo

Applied network visualization techniques to market basket analysis using transactional datasets to gain insights into customer behavior and purchasing patterns. Co-authored a paper titled “Exploratory Analysis on Market Basket Data using Network Visualization,” published at BrasnAm 2023.

Undergraduate Research Project - Network Visualization at Universidade de Sã o Paulo

Applied network visualization techniques to Market Basket Analysis by exploring transactional datasets to gain insight into customer behavior and purchasing patterns. Co-authored the paper “Exploratory Analysis on Market Basket Data using Network Visualization,” published at Brasn am 2023.

Undergraduate Research Project - Visualization Techniques for Decision Support Systems at University of Sã o Paulo

Developed a dynamic web platform for visualizing large-scale temporal graphs across domains including healthcare, commerce, and academic research. Built frontend features such as zoom-to-fit, node color customization via legend interaction, and UX improvements to streamline navigation and usability. Co-authored “Large NetVis: Visual Exploration of Large Temporal Networks Based on Community Taxonomies,” published at IEEE VIS 2022.

Undergraduate Research Project - Visualization Techniques for Decision Support Systems at Universidade de Sã o Paulo

Developed a dynamic web platform to support visualization of large-scale temporal graphs across healthcare, commerce, and academic research environments. Built front-end features for better interpretation of network visualizations, including zoom-to-fit, node color customization via legend interaction, and UX improvements for streamlined navigation. Co-authored “Large NetVis: Visual Exploration of Large Temporal Networks Based on Community Taxonomies,” published at IEEE VIS 2022.