INDUSTRY ​EXPERIENCE

As a multidisciplinary professional, I have gained ​experience across various industries, working with big ​brands and startups.

HEALTHCARE

REAL ESTATE

DECOR

E-COMMERCE

FAshion

FORMAL ​EDUCATION

My educational background includes an MBA in Big Data ​(Data Science) and a bachelor's in Communication, providing ​a robust foundation in data analysis and communication ​strategies. This unique combination enhances my ability to ​apply Data Science, Machine Learning, and Natural ​Language Processing techniques effectively.

SKILL Su​mmary

MACHINE LEARNING

Data Visualizati​on

• Natural Language Processing with ​Transformer Models and classic ​techniques (POS Tagging, NER, BoW, ​TF-IDF, N-grams, Word2Vec etc.)
• A​PI integration
• Random forests
  
• Logistic/lin​ear regression
  
• Cluster​i​ng algorithms
  

• Streamlit dashboards
  
• Tableau
• Matplotlib
• Seaborn
• Plotly

Feature Engineering

Data Engineering

• SQL
• Mongo DB
• ET​L​ pipelines

Programming TOO​LS

• macOS
  
• Python
  
• HTML
• Docker
• git, bitbucket, github, gitlab
• Confluence
• Jira

LA​NGUAGES

• Portuguese
• French
• Eng​lish
• Ge​rman (A1​)​

• Dimensionality Reduction
  
• Feature Derivation
  
• Embeddings
  
• Feature Selection methods
  

CLOUD

• Google Cloud
• Azure

PYTHON PACKAGES

• pandas, numpy
  
• tensorflow, keras, sklearn
  
• opencv, pillow
  
• huggingface, nltk, spaCy
  
• seaborn, matplotlib, streamlit
  

PLAYGROUND

Click on the images to open the demos.

CHICLYTIC

ChicLytic (@ChicLytic) analyzes fashion ​trends using data science. I process ​fashion data from social media and retail, ​uncovering key trends and insights. Built ​with Python and machine learning, it tracks ​emerging styles in real-time. Ideal for ​fashion professionals and enthusiasts ​looking to stay ahead of the curve with ​data-driven fashion predictions.

Personal Fashion ​Advisor

The Personal Fashion Advisor specializes ​in providing users with personalized ​fashion recommendations that align with ​their style preferences, lifestyle, and ​current fashion trends. It uses the GPTs ​tool provided by OpenAI to act as a ​personal stylist assistant.

THE MARKETER BOT

Chat with a bot who acts as a Marketing ​Specialist. This project was built using the ​Meta Llama 3 family of large language ​models and can sustain marketing-related ​conversations using Streamlit, the Hugging ​Face inference API, and prompt​ engineering​ techniques.

ME​dical NER

Named Entity Recognition (NER) identifies ​and classifies entities in text into categories ​like names, locations, and medical terms, ​aiding tasks like clinical decision support ​and medical coding.

Patient Feedback ​Analysis

Analyze patient feedback data with this ​NLP-powered dashboard. This tool ​processes text data from patient surveys, ​providing immediate insights into sentiment ​and key themes. Built with Streamlit and ​Hugging Face, it ensures privacy by ​processing data without storing it. Perfect ​for healthcare providers looking to enhance ​patient satisfaction through actionable ​insights.

LET’s CONNECT