Organizing committee member

• Mar 2022 - Present

Sponsors and Partnerships Sponsors and Partnerships

Researcher

• Aug 2021 - Present

Data Product M.

• Aug 2019 - Aug 2021

● Facial recognition model for generating a private key derived from users’ faces based on prime numbers logic, extracted from their embeddings. ● Age and gender classification models. ● Hologram detection. ● Image processing to frame selection based on several features. ● Responsible for scheduling meetings, interacting with suppliers, reviewing deliverables and coordinating the technical teams' activities. ● Business intelligence through statistical analysis and mathematical modeling. Show less

Data Scientist

• Feb 2018 - Jun 2019

● Posts’ sentiment analysis. ● NLP to find interests in comments' audience through posts to the different verticals, using LDA, LSI, NMF, K-nearest neighbors algorithms. ● Statistical analysis to different areas, ranging from: comercial planning, social media, editorial video and political concerns. ● Posts’ sentiment analysis. ● NLP to find interests in comments' audience through posts to the different verticals, using LDA, LSI, NMF, K-nearest neighbors algorithms. ● Statistical analysis to different areas, ranging from: comercial planning, social media, editorial video and political concerns.

Data analyst

• May 2016 - Aug 2017

Seasonal product analysis. Price-demand elasticity analysis for top products based on country. Model to accurately forecast inventory demand based on historical sales data to make sure consumers of over one hundred bakery products aren’t staring at empty shelves, while reducing the amount spent on refunds to store owners with surplus product unfit for sale. ● Feature engineering. ● Product clustering. ● Models: XGboost, linear and extra trees regressor and weighted average. Show less

BI analyst

• Aug 2015 - Feb 2016

● Customer Lifetime Value model. ● Churn prediction model. ● Customers classification according to their strategic importance to the company based on purchases and orders frequency. ● Customer Lifetime Value model. ● Churn prediction model. ● Customers classification according to their strategic importance to the company based on purchases and orders frequency.