Arthur Mello

- Developed a product search engine on Vertex AI, using LLMs, RAG, prompt engineering and chaining techniques - Developed many POCs with LLMs. Ex.: an image-based skincare recommendation engine and a text-to-SQL chatbot

• Developed multiple Generative AI demonstrators and POCs using GCP for text and image generation • Developed a classification and entity extraction tool in Python for process automation, using LLMs • Built a P&L of the digital activities of a beauty player, making suggestions on how to streamline them across regions

• Developed a revenue forecasting model that reduced baseline error by 10%, using a seasonality clustering method • Increased utilization rate of discount coupons by 30%, using an allocation algorithm to estimate the likelihood that each user will use each coupon • Developed a WebApp allowing CRM to launch monthly allocations for discount coupons, giving them autonomy and saving time for the Data Science team. • Analysed data to understand segments of customers and measure the performance of marketing campaigns • Managed team of consultants, making sure their projects run smoothly, that they are happy with the company and that they achieve their goals and learn constantly • Created dashboards to follow NPS drivers, customer journeys and campaign results • Calculated price elasticity coefficients at SKU level, to help optimize promotions • Segmented website navigation sessions using topic modelling techniques, in order to improve CRM campaign targeting • Used web scraping and sentiment analysis to gather customer reviews and get improvement insights for each point of sale • Conducted multiple workshops with different kinds of stakeholders to explain data concepts and analyses Industries: Online betting, retail and luxury Tools: SQL (Athena, BigQuery and Snowflake), Python, PySpark, Dataiku DSS, Tableau, Google Data Studio and Google Analytics

Scoring for Marketing course for 2nd year Master's students

Tutoring for Data Science / Data Analysis students

• Implemented the new Data Warehouse on PostgreSQL for displaying KPIs on Google Data Studio; • Automated reports and dashboards using Python and Google Sheets; • Analysed data from different sources to identify trends and opportunities