
Data Scientist in Machine Learning Operations
1 week ago
**Job Opportunity:**
As a Data Scientist in Machine Learning Operations, you will be responsible for developing, training, and validating predictive models using machine learning techniques. You will collaborate with data engineers and business teams to define data requirements and success metrics, deploying models into production using best practices.
**Key Responsibilities:
- Develop automated pipelines for model training, testing, monitoring, and retraining.
- Optimize model performance and ensure scalability and reliability.
- Monitor model drift, performance degradation, and ensure continuous improvement.
- Implement CI/CD practices for machine learning workflows.
**Required Skills and Qualifications:
- Strong proficiency in Python (Pandas, NumPy, Scikit-learn, PyTorch/TensorFlow).
- Experience with ML Ops tools/frameworks (MLflow, Kubeflow, Airflow, SageMaker, Vertex AI, or Azure ML).
- Good understanding of data engineering concepts (ETL, data pipelines, APIs).
- Hands-on with containerization and orchestration (Docker, Kubernetes).
- Knowledge of cloud platforms (AWS, GCP, or Azure) for ML model deployment.
**Ideal Candidate Profile:
- Bachelor's/Master's degree in Computer Science, Data Science, Statistics, or related field.
- Experience in handling large-scale data pipelines and real-time model serving.
- Exposure to feature stores and automated model monitoring.
- Strong problem-solving, analytical, and communication skills.
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