We are looking for a Senior Data Scientist who gets bored just training models...This is a hybrid position, 2x on site, per week.You'll be working on an AI Platform within the banking sector, on real problems — messy data, unclear questions, no perfect datasets. You'll need to think, structure, test, and iterate. Not just execute.What you'll actually do- Take ambiguous problems and turn them into workable solutions - Work across the full ML lifecycle (data → model → production) - Decide how to approach a problem — not just implement it - Build models, test ideas, fail, iterate, improve - Work closely with data and business — no hand-holding, no predefined roadmapRequirements:- +6 Years of experience. - Excellent understanding of machine learning techniques and deep learning algorithms (such as k-NN, Naive Bayes, SVM, Random Forests, MLP, LSTM, etc.) and libraries (such as pandas, numpy, tensorFlow and Scikit-Learn). - Experience with common data science toolkits, such as Python or R. Excellence in at least one of these is highly desirable - Good applied statistics skills, such as distributions, statistical testing, regression, etc. - Very good scripting in Python and programming skills - Experience in Apache Spark, Databricks, and distributed training - Proficiency in using query languages such as SQL, Spark SQL, etc. - Experience with NoSQL databases, such as MongoDB, CosmosDB, etc. - Familiarized with container technologies like Docker and Kubernetes - Experience with data visualization tools - Data-oriented personality - Data Analyst with Proven Expertise in Experience in Reinforcement Learning, LLM, and Prompt Engineering - Experience in generative AI / reinforcement learning/ graph algorithms - Experience in neural networks and monitoring of models deployed in production - Fluent in Portuguese