VAGA AFIRMATIVA PARA MULHERES - SENIOR DATA SCIENTIST (31939)The LA AI & Data Center of Excellence seeks a highly skilled and motivated Senior Data Scientist to join our team. This role focuses on developing and deploying cutting-edge AI solutions, emphasizing automation, software engineering best practices, and production-ready code. This role requires proficiency in Python programming and experience with various machine learning, deep learning, generative and agentic AI.The successful candidate will work on projects across diverse business units, directly impacting critical decision-making and driving innovation.You will lead the development of intelligent systems with a strong emphasis on software and AI engineering best practices, automation, and continuous delivery.Experience and knowledge (Mandatory):Strong experience in Data Science, Machine Learning, or AI Engineering roles, demonstrating a history of delivering impactful AI solutions.Expert-level Pythonprogramming, including Pandas, Polars, NumPy, Scikit-learn, TensorFlow, PyTorch, Keras, and experience with RESTful API development. Experience with Flask/FastAPI for API development is a plus.Strong software engineering foundation:Version control (Git), unit testing, CI/CD pipelines, Clean Code principles, and containerization (Docker, Kubernetes).Strong understanding of programming logic and object-oriented programming (OOP) principles to design modular, reusable, and maintainable code structures.Proven experience inend-to-end ML (Machine Learning) lifecycle: data preparation, model training, tuning, inference, deployment, monitoring, and retraining.Data handling expertise:Extraction, cleaning, transformation, and loading (ETL) from various sources (relational and non-relational databases, cloud storage, APIs). Experience with SQL, NoSQL and vector databases.Machine Learning & Deep Learning:Supervised and unsupervised learning techniques, including regression, classification, clustering, time series, and NLP (Natural Language Processing).Natural Language Processing (NLP): Experience with text preprocessing, pre-trained models (BERT, Roberta), fine-tuning, and NLP libraries (scikit-learn, spaCy, NLTK, Gensim).Experience withGenerative AI(e.g., LLMs, prompt engineering, fine-tuning, RAG pipelines).Experience withcloud platforms: Azure (preferred), GCP or AWS, including their respective AI/ML services (e.g., Azure AI services).Strong understanding of model evaluation, feature engineering, and hyperparameter tuning.Experience and knowledge (Desirable):Hands-on experience withmulti-agent systems and autonomous AI agents (e.g., LangChain, AutoGen, LangFlow), including the Model Context Protocol (MCP).Familiarity withdata engineering: experience with data warehousing, and big data technologies (Spark, Hadoop, Databricks).Experience withMLOpstools and practices: MLFlow, Kubeflow, Docker, Kubernetes, Jenkins, GitHub Actions, Azure DevOps.Experience working with knowledge graphs and graph-based data representations, including tools like Neo4j, RDF, SPARQL, Stardog or graph neural networks for reasoning and relationship modeling.Domain knowledge (e.g.: experience in industry, laws, HR, marketing, etc.).Ability to assess the business impact and profitability of AI models, including cost-benefit analysis, ROI estimation, and value tracking post-deployment.Ph.D. in a relevant field.Qualifications:Bachelor’s or Master’s degree in Computer Science, Data Science, Computer Engineering, Software Engineering, Information Technology, Mathematics, or Physics.Personality and working method: team player, problem-solving, analytical thinking, pro-active, self-taught, and resilient.Strong communication & collaboration:ability to translate technical insights into accessible information for diverse audiences. Proven ability to work effectively in agile, cross-functional teams.Continuous learning:Passion for staying current with AI advancementsLanguages: Portuguese (Brazilian) and fluent in English. German is a plus.- Prazo:04/08/2025
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