Master's Scholarship Researcher – Data Scientist, NLP, Semantic Search Systems

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🔥 1 hour ago

🇧🇷 Brazil – Remote

💵 R$9k / month

⏰ Full Time

🟡 Mid-level

🟠 Senior

📊 Data Scientist

👻 Ghost score 18%

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Sistema Fibra

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 1972

🤝 B2B

🤝 Non-profit

📚 Education

B2B • Non-profit • Education

Sistema Fibra is a civic organization based in Brasília that focuses on enhancing the competitiveness of industries and entrepreneurship through representation and support. It brings together various entities, including Sesi, Senai, and IEL, to promote industrial growth and workforce development in Brazil.

📋 Description

• Perform text preprocessing and enrichment, including cleaning, tokenization, lemmatization, and noise removal • Extract relevant features for NLP models • Create document and query embeddings using Sentence-BERT, OpenAI Ada, or similar models • Store and index embeddings in vector databases • Develop semantic search, information retrieval, and RAG application pipelines • Implement query, embedding, vector search, optional re-ranking, and retrieved-context utilization workflows • Evaluate retrieval and generated-answer quality using metrics such as recall@k and MRR • Adapt pre-trained models in PyTorch or TensorFlow for classification, similarity, and information extraction • Experiment with architectures such as transformers and simple neural networks • Document pipelines, technical decisions, and experiment results • Use Git for code version control

🎯 Requirements

• Master's degree in progress or completed • Degree in Computer Science, Computer/Software Engineering, Information Systems, Statistics, Applied Mathematics, Electrical Engineering, Data Science, or related fields in the Exact Sciences and Engineering disciplines • Python programming proficiency, including typing, data manipulation (pandas/Polars), and virtual environment usage • Practical experience with NLP, including tokenization, stemming/lemmatization, stopword removal, and vectorization (TF-IDF, word2vec, or embeddings) • Applied knowledge of embeddings, semantic search, and RAG techniques, including Sentence-BERT and vector databases such as FAISS, ChromaDB, Pinecone, or Qdrant • Experience with at least one deep learning framework (PyTorch or TensorFlow), sufficient to load pre-trained models and perform basic fine-tuning • Understanding of analytical pipelines and experimentation in data science applied to NLP • Git version control • Experience with generative models (LLMs), prompt engineering, and response evaluation is a plus • Knowledge of PostgreSQL, MongoDB, and Redis is a plus • Experience with real-world academic or professional projects involving documentation and testing is a plus

🏖️ Benefits

• Scholarship stipend: BRL 9,000.00 • Remote work • Availability for 40 hours per week • 9-month duration

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