Data Scientist @ Todyl. Previously, Research Scientist @ Georgia Tech. CS Master & PhD @ UFPR. Machine Learning & Cyber Security Scientist and Researcher.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Todyl
Data Scientist
June 25, 2026 – Present
CotB-MalFi-Dataset
October 24, 2023 – October 24, 2023
Financial malware dataset and code
View ProjectCapyMOA
September 1, 2023 – Present
Enhanced machine learning library tailored for data streams, featuring a Python API integrated with MOA backend support. This unique combination empowers users to leverage a wide array of existing algorithms efficiently while fostering the development of new methodologies in both Python and Java.
View ProjectFast-Furious-Malware-Data-Streams
May 16, 2022 – May 16, 2022
Fast & Furious: Modelling Malware Detection as Evolving Data Streams
View Project2021-Machine-Learning-Security-Evasion-Competition
September 28, 2021 – September 29, 2021
2021 Machine Learning Security Evasion Competition
View ProjectTeamUFPR-IDPT2021
July 4, 2021 – September 21, 2021
TeamUFPR at IDPT 2021. Complete set of results and source code.
View Projectmlsec2020-needforspeed
September 24, 2020 – September 24, 2020
MLSEC 2020: Need for Speed Malware Detection Model
View Projectml-cybersecuritiy-course
July 26, 2019 – September 5, 2019
Machine Learning applied to Cyber Security Course
View Projectbrazilian-malware-dataset
May 25, 2018 – November 30, 2020
Dataset containing thousands of malware and goodware collected in the Brazilian cyberspace over years.
View ProjectCultural Fit Analysis
The candidate's projects are heavily concentrated in machine learning for cybersecurity, indicating a strong niche interest. While this depth is valuable, the lack of diversity in project domains might suggest a narrower scope of experience outside this specific area. The target role 'Data Scientist' is broad, and the candidate's current experience aligns well with data science applications in security. However, without more diverse projects or experience, it's hard to assess adaptability to different data science domains.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. No psychometric test results or interview feedback provided.