Business Development and Growth optimization using data, statistics, business acumen and artificial intelligence (AI).

-- Thesis: "Generalized Additive Mixed Models for Online Learning Data"- Key words: psychometrics, item response theory (IRT models), generalized linear mixed models (GLMMs), generalized additive mixed models (GAMMs), adaptive learning environments, estimators' biases and variance, goodness of fit, learning modelling

- My activities in the Advanced Analytics division involve dealing with spending behavior (from cardholder's and merchant's point of view) on multiple levels. From manipulating large data sets (+1 TB) and developing many statistical/machine learning models and methods, I extract business and economic insights; not limited to the data products available on our portfolio, but also developing new products, doing R&D and consulting activities at clients.In addition to that, I usually work with semi-structured information, which means that I often challenge and contextualize my results with economics time series (interest rates, rent prices, inflation...) and data available from merchants' balance sheets.Visual display of information, storytelling and presenting/explaining complex results to the non-technical community is also a big part of what I do.- Modelling products & techniques include: Agile mindset towards modelling and coding development, Pre&Post Analysis, Market Share and sales prediction, segmentation & clustering, recommender systems, probabilistic solutions and algorithms to supervised and unsupervised problems, time-series analysis, customer behavior rating (internet, card usage), market basket analysis, lifting and affinity.- Computational tools include: WPS/SAS, Python, R, SQL, Hadoop environment, Hive, Unix, Excel, VBA, Angoss, Domo- Machine learning models include: classification trees (CART), Naive Bayes, Logistic Regression, Mutiple Regression- Industries that I have done projects to: Grocery Stores and Wholesale Clubs, Oil & Gas, Issuers, Fast Food chains, Clothing Retail, Telecommunications, Electronics and Appliances, Beauty and Personal Care, Banks.

- Short assignment in Australia;- Loyalty business;- Helped, from end-to-end (business case, data retrieval, variable creation, model assessment and technical/business deck creation, presentation) develop a solution to an attrition (churn) issue on a MasterCard’s biggest partners.

I first started at Banco Safra as an intern, moving up a month later to Junior Analyst, then Credit Risk Associate Trainee and lastly Sr. Analyst/Data Scientist.Sr. Analyst/Data Scientist (Jan/2016 - Oct/2016):- Lead generation using information already hosted in the bank and acquiring only target variables from external bureaus of information;- Extensive research involving clustering/segmentation and scoring of the leads generated;- Data science tools/practices include: data cleansing, statistical & managerial clustering, logistic regression, transitional matrix, validation and revenue prediction;- Dashboards, reports and presentations to higher management and stakeholders;- Basil II/III - Economic Capital Modelling;- Technical reports and scientific writing (ICAAP) to the Central Bank of Brazil;- Computational tools include: Excel, VB/VBA, R, SQL and SAS.Credit Risk Associate Trainee (Jan/2015 - Dec/2015):- My job rotation included: Safra´s local branch, Products, Credit Analysis, Planning and Forecasting, Credit Monitoring, Legal, Accounting, Credit Risk;- Last project: Natural Language Processing news platform for commercial managers from the Corporate and Large Corporate divisions. Junior Analyst (Sep/2014 - Dec/2014):- Tasks were in the credit modelling andcollateral management fields. I was part of a team of Full Stack DevelopersIn particular, I developed statistical/predictive techniques to deal with unstructured/structured information and web scraping tools. Meetings were held with different stakeholders across Banco Safra in order to gather domain knowledge and user-experience insights on a weekly basis.- Programming languages included SAS, VBA, SQL, Visual Basic and MATLAB.Intern (Jun/2014 - Aug/2014):- I worked in projects associated with allowance for doubtful accounts and credit modelling; mostly developingapplications and automated processes using large datasets on SAS, VBA and SQL.

- Stock Borrowing & Lending department. - Tasks included: Backoffice duties (reports to clients and solving problems related to stock borrowing and lending), following financial news (sources include the web, newspapers and Bloomberg station), Broker-Dealer duties (deal on the daily basis with major and minor players in the stock market regarding stock availability and filling direct BTG Pactual clients needs), improve and develop new methods and existing routines through Excel VBA.

- Along with Dr. Edward Wollack at the Observational Cosmology Laboratory, we developed numerical models to be applied to assist research involving Electromagnetic experiments, such as analysis of dielectric materials and waveguides. - Tasks include: Mathematical Physics, Partial Differential Equations, Numerical Analysis, MATLAB Programming.

- I tutored classes with up to five students in the following topics: Calculus I & III, Numerical Analysis, Complex Variables, Abstract Algebra, Linear Algebra and Statistics.

- Under the supervision of Dr. Lin-Ching Chang, I developed a computer program in MATLAB environment that executed the following routine: download, analysis and classification of solar images. The project's focus was create a computer mechanism that could classify among solar images, those with coronal mass ejections evidences.

Scholarship Holder for the program Science Without Borders (Ciências sem Fronteiras).

- I was part of a group organized and under the supervision of Dr. Vladimir Belitsky (IME-USP) and Dr. Yuri Suhov (Oxford), in which we developed a High Frequency Trading (Automated Trading) program.- Initially I worked as a C++ programmer and then as a quantitative analyst.