Danilo Nunes
Data AnalystAI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Software Engineer | Machine Learning Engineer
Sou um profissional com espírito empreendedor e muito versátil. Possuo mais de 15 anos de experiência na área de TI executando diversos papéis como: desenvolvedor, consultor de negócios, gerente de projetos, engenheiro de software e data scientist. Também possuo experiência em liderança de equipes além de ter atuado como docente no ensino superior. Atualmente sou Data Scientist em uma startup focada em desenvolver produtos utilizando inteligência artificial onde sou um dos Co-Founders. Possuo experiência em diversas áreas como big data, desenvolvimento, banco de dados, data mining e sistemas operacionais. Recentemente tenho focado em machine learning especialmente em aplicações utilizando deep learning e os seguintes frameworks: Caffe, Torch e Theano. Tenho atuado com Data Science especialmente com tecnologias envolvendo: R, Matlab, Hadoop, Spark, e HBase. Além disso, no âmbito acadêmico sou um estudante de doutorado e minha pesquisa envolve as áreas de visão computacional e processamento de linguagem natural.
FEI
Doctor of Philosophy (Ph.D.) student, Inteligência Artificial
January 1, 2013 – January 1, 2016
FEI
Master of Science (MS), Inteligência Artificial
January 1, 2007 – January 1, 2009
USCS - Universidade Municipal de São Caetano do Sul
Bacharelado, Ciências da Computação
January 1, 2002 – January 1, 2005
Overjet
Machine Learning Engineer
February 1, 2022 – Present
Machine Learning Engineer
March 1, 2021 – October 1, 2022
Dr. Opinion
Machine Learning Engineer
February 1, 2020 – February 1, 2021
Laguro
Machine Learning Engineer
June 1, 2019 – December 1, 2019
Qume, Inc.
Software Engineer
August 1, 2018 – May 1, 2019
B2W Digital
Machine Learning Engineer
April 1, 2016 – July 1, 2018
boolabs
Co-Founder & Data scientist
November 1, 2013 – April 1, 2016
São Paulo e Região, Brasil
UNIP
Professor
February 1, 2008 – July 1, 2008
Advanced ITeam Soluções e Serviços de TI Ltda
Consultor de negócios
May 1, 2006 – May 1, 2014
São Paulo e Região, Brasil
Grupo ASSA
Consultor
October 1, 2004 – May 1, 2006
Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
Coursera
June 24, 2026 – Present
Structuring Machine Learning Projects
Coursera
June 24, 2026 – Present
Sequence Models
Coursera
June 24, 2026 – Present
Deep Learning Specialization
Coursera
June 24, 2026 – Present
Neural Networks and Deep Learning
Coursera
June 24, 2026 – Present
Convolutional Neural Networks
Coursera
June 24, 2026 – Present
Cultural Fit Analysis
The candidate has a diverse professional background, including roles in startups (Dr. Opinion, Laguro, Qume, boolabs) and larger tech companies (Pinterest, B2W Digital). The academic background and continuous learning through certifications suggest a growth mindset. The transition from Software Engineer/Consultant to Data Scientist/Machine Learning Engineer demonstrates adaptability. However, the target role is 'Data Analyst', while the candidate's experience is heavily skewed towards 'Machine Learning Engineer' and 'Data Scientist'. This indicates a potential mismatch in the specific day-to-day responsibilities and depth of analytical vs. model development work. While the underlying skills are related, the focus of the roles differs significantly, which could impact cultural fit for a pure Data Analyst position.
Soft Skills & Operational Fit
The candidate's resume indicates a strong technical background with a focus on Machine Learning and Data Science. The co-founder role suggests entrepreneurial drive and problem-solving skills. The professor role indicates an ability to explain complex concepts. However, without psychometric test results or interview data, specific soft skills like teamwork, stress handling, or communication clarity cannot be objectively assessed. The descriptions for recent roles are brief, limiting insight into operational fit beyond technical contributions.