I’m Pedro Albuquerque, Staff Data Scientist. I build interpretable and impactful AI causal models using ML and econometrics. pedro.melo.albuquerque@gmail.com
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
CS495-Mapping-Best-Empirical-Models
April 10, 2026 – Present
CS495-Mapping-Best-Empirical-Models — GitHub repository
View ProjectSemeAD_Arbitagem
April 9, 2018 – April 10, 2018
Projeto pra o SemeAD em São Paulo, Dead line de submissão 16/07/2018
View ProjectEconometriaFinanceira1
January 22, 2018 – April 20, 2018
Material do curso de econometria financeira 1
View ProjectCaviar
January 15, 2018 – January 15, 2018
Conditional Autoregressive Value-at-Risk: all flavors of CAViaR.
View ProjectqLearningFinance
January 12, 2018 – March 31, 2019
Artigo sobre q-learning e portifólios financeiros
View ProjectRMCriteria
November 28, 2016 – September 16, 2019
RMCriteria is a package to solve Multiple-Criteria Decision Analysis (MCDA) problems. For now, it only supports Promethee methods, but other methods may be developed in the future.
View ProjectCultural Fit Analysis
The candidate's projects are heavily focused on quantitative finance and econometrics, which aligns with certain aspects of a Data Scientist role, particularly in financial domains. However, the lack of diverse project types or team-based projects makes it difficult to fully assess broader cultural fit or adaptability to varied data science challenges. The candidate's experience level is listed as 0, suggesting a junior profile, which might not align with senior-level expectations without further validation.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. No psychometric test results or interview feedback provided.