Data Science | SR

Accountabilities:: Develop predictive models and machine learning algorithms to solve complex business challenges, taking ownership from data exploration and experimentation through validation and interpretation, with a focus on measurable outcomes. Apply supervised, unsupervised, and deep learning techniques using Python and leading data science libraries, including Scikit-learn, XGBoost, and LightGBM. Design and execute experiments using tools such as Jupyter, Databricks, and MLflow, ensuring robust model evaluation and reproducible experimentation. Evaluate the performance of RAG and language-model-based systems using quality, cost, latency, and semantic metrics, including BLEU, ROUGE, and related evaluation approaches. Build text-ingestion pipelines for vector databases, including solutions using AWS OpenSearch, and develop APIs with LangChain and LangGraph integrated with OpenAI and AWS Bedrock. Work with AWS services such as S3, Lambda, Parameter Store, and Secrets Manager, while contributing to serverless and containerized architectures across AWS and Azure. Leverage Azure Document Intelligence and other cloud services for document extraction, processing, and AI-powered workflows. Requirements: Solid professional experience with Python and strong practical knowledge of data science and machine learning. Hands-on experience developing and deploying machine learning models using libraries such as Scikit-learn, XGBoost, and LightGBM. Proven experience with Large Language Models (LLMs), Generative AI, RAG architectures, and agent-based AI solutions. Practical experience working with Databricks and MLflow for data science, experimentation, and model development workflows. Experience with LangChain and LangGraph for building LLM-powered applications and agentic solutions. Experience working with AWS Bedrock and familiarity with the broader AWS ecosystem. Knowledge of language-model evaluation metrics such as BLEU and ROUGE is considered a plus. Working knowledge of both AWS and Azure cloud environments, including cloud-native, serverless, and containerized architectures. Strong analytical and problem-solving abilities, with the capacity to translate complex technical challenges into practical solutions. Ability to work independently, communicate technical concepts clearly, and collaborate effectively with multidisciplinary teams. Benefits: Remote work opportunity for professionals based in Brazil. Opportunity to work on advanced Machine Learning, Generative AI, LLM, and RAG initiatives. Exposure to modern AI and cloud technologies, including AWS, Azure, Databricks, LangChain, LangGraph, and MLflow. Work on technically challenging projects with a strong focus on innovation and measurable business impact. Opportunity for continuous professional development and exposure to emerging trends in Artificial Intelligence and Data Science. Collaboration within a technology-driven environment that values knowledge sharing and the development of advanced technical skills. Competitive compensation and benefits package, according to the employment arrangement and local market practices.