Especialista de Ciência de Dados
New
BrazilFull-TimeSenior
Salary not disclosed
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Job Details
- Required Skills
- AWSGCPKerasMachine LearningPyTorchAzureData scienceTensorflowDatabricks
Requirements
- Degree in Computer Science, Statistics, Engineering, Mathematics, Physics, or related fields.
- Strong experience in Data Science, Machine Learning, and advanced analytics projects.
- Solid knowledge of data infrastructure, Big Data environments, and data visualization tools.
- Experience building descriptive, predictive, and prescriptive models, including deep learning frameworks (TensorFlow, Keras, PyTorch, etc.).
- Proven experience deploying models into production and applying testing methodologies for data products.
- Experience with cloud-based machine learning platforms such as AWS, Azure, or Google Cloud.
- Experience contributing to or leading software/data projects with production-level impact.
- Strong leadership skills in delivering data science solutions within cross-functional teams.
Responsibilities
- Develop and maintain advanced machine learning models, including supervised and unsupervised learning, time series forecasting, reinforcement learning, and optimization techniques such as linear programming.
- Lead data science initiatives from problem definition through to deployment, ensuring end-to-end delivery of robust analytical solutions.
- Conduct deep business immersion sessions with stakeholders to identify needs, translate them into data-driven solutions, and generate actionable insights.
- Build and automate scalable data science pipelines and workflows using modern platforms such as Databricks.
- Ensure governance, quality, and reliability of models, calculations, and analytical outputs in production environments.
- Collaborate with external partners and internal teams on strategic projects, ensuring knowledge transfer and internal capability building.
- Structure and document analytical processes, data flows, and model architectures to ensure clarity and scalability.
- Lead data science decisions within squads, ensuring alignment with business priorities, timelines, and technical excellence.
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