Senior Data Science Engineer

1 dia atrás

Rio de Janeiro, Rio de Janeiro, Brasil beBeeMachineLearning Tempo inteiro R$90.000 - R$120.000
Machine Learning Specialist Position

We are seeking a highly skilled Machine Learning Specialist to develop and deploy advanced predictive models from concept to production.

The ideal candidate is proficient in building, deploying, and maintaining ML solutions that deliver tangible business impact.

Key Responsibilities:
  • Design, build, and deploy machine learning models using Python (Pandas, NumPy, scikit-learn, TensorFlow, PyTorch) for predictive analytics and forecasting.
  • Apply advanced time series techniques (ARIMA, SARIMA, Prophet, LSTM/RNNs) to forecast and model temporal data for informed decision-making.
  • Build and manage ML pipelines for training, validation, deployment, and monitoring using tools like MLflow, Kubeflow, or cloud-based ML services for efficient MLOps.
  • Monitor performance, detect drift or bias, and iterate on models to improve accuracy, reliability, and scalability.
  • Develop impactful features, especially for time series and structured datasets.
  • Analyze datasets and communicate findings through clear visualizations (Matplotlib, Seaborn, Plotly) to guide strategic decisions.
  • Collaborate with product managers, data scientists, engineers, and business stakeholders to align ML solutions with real-world needs and goals.
Required Skills:
  • Advanced Python programming skills for ML (Pandas, NumPy, scikit-learn, TensorFlow, or PyTorch).
  • Strong understanding of supervised, unsupervised, and deep learning techniques.
  • Expertise in time series forecasting and handling temporal data.
  • Experience with MLOps practices for production-scale deployments.
  • Familiarity with cloud ML services (AWS SageMaker, Azure ML, Google Cloud AI Platform).
  • Strong problem-solving and communication skills.
Preferred / Nice to Have:
  • Solid SQL skills and experience with data extraction/transformation.
  • Knowledge of modern data engineering tools (Airflow, Spark, dbt, Snowflake, or similar).
  • Experience with CI/CD for ML workflows.

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