Data Scientist

• Higher university education in Computer Science, Mathematics, Statistics, Physics, Engineering, or a related field. A Master's or PhD in Data Science, Artificial Intelligence, or related areas will be valued.
• Demonstrable professional experience of at least 5 years as a Data Scientist or in a similar role, with a clear focus on the development and integration of machine learning and deep learning models.
• Deep knowledge of machine learning algorithms (supervised and unsupervised), including clustering, classification, regression, and dimensionality reduction techniques.
• Hands-on experience in the development of deep learning models using frameworks such as TensorFlow, PyTorch, or Keras.
• Proficiency in programming languages such as Python (preferably) or R, and experience with relevant data science libraries (NumPy, Pandas, Scikit-learn, NLTK, SpaCy, etc.).
• Experience in the application of NLP techniques for text analysis.
• Knowledge and experience in the integration of models into production environments and the software development lifecycle (MLOps).
• Familiarity with cloud platforms (Azure, Google Cloud) and their services related to machine learning and data analysis.
• Ability to perform proofs of concept (POC) and feasibility studies autonomously.
• Excellent communication skills, both oral and written, to explain complex technical concepts to diverse audiences.
• Analytical capacity, problem-solving, and attention to detail.
• Proactivity, autonomy, and a strong orientation toward results.

We are looking for a highly qualified Data Scientist with a solid track record in the development and integration of machine learning models to join our team.

If you are passionate about the world of data, have proven experience in the design, training, and validation of machine learning and deep learning models, and are looking for a dynamic environment where you can apply and expand your knowledge, this is your opportunity!

• Design, train, and validate cutting-edge machine learning and deep learning models, ensuring their robustness and performance.
• Actively participate in projects covering various modeling techniques, including clustering, classification, regression, and anomaly detection, to extract valuable knowledge from complex data sets.
• Apply advanced Natural Language Processing (NLP) techniques for information extraction, automatic summarization, and semantic analysis, unlocking the potential of textual data.
• Integrate developed models into efficient and scalable production pipelines, guaranteeing their correct implementation and operation in real-world environments.
• Lead and execute feasibility studies and proofs of concept (POC) to explore and validate new use cases and business opportunities based on artificial intelligence.
• Exhaustively document developed solutions, including methodologies, results, and technical specifications, facilitating understanding and adoption by other teams.
• Collaborate closely with multidisciplinary teams, including data engineers, developers, and business analysts, to ensure project alignment with the strategic objectives of the company and the client.
• Participate in the training and capacity building of end users and technical teams, transferring knowledge and fostering a data culture within the organization.
• Actively contribute to the proof of concept (POC) phase, functional validations, and deployments in cloud environments such as Azure and Google Cloud, applying industry best practices.