Data Science Professional

2 weeks ago


Aurangābad, India beBeeArtificial Full time

Job Title: Data Science EngineerOur team is currently seeking a skilled Data Science Engineer with 3–5 years of hands-on experience in designing, developing, and deploying AI/ML solutions in cloud environments. The ideal candidate will have strong proficiency in Python, experience with both Azure and AWS, and a solid understanding of MLOps practices.The primary responsibilities include:Designing and implementing scalable AI/ML models for banking applications (e.g., fraud detection, credit scoring, customer segmentation).Deploying and managing models in production using Azure ML and AWS SageMaker.Collaborating with data scientists, software engineers, and DevOps teams to operationalize ML workflows.Building and maintaining CI/CD pipelines for ML model deployment and monitoring.Ensuring compliance with data governance, security, and regulatory standards.Optimizing model performance and resource usage in cloud environments.Documenting processes, models, and deployment strategies for internal knowledge sharing.Required skills include:Programming: Strong Python skills, including libraries like Pandas, NumPy, Scikit-learn, TensorFlow or PyTorch.Cloud Platforms: Hands-on experience with Azure ML, AWS SageMaker, and cloud-native services (e.g., Lambda, EC2, S3, Azure Functions).MLOps: Familiarity with ML lifecycle tools (MLflow, Kubeflow, Airflow), containerization (Docker), and orchestration (Kubernetes).Deployment: Experience deploying models as REST APIs or batch jobs in production environments.Version Control & CI/CD: Git, GitHub Actions, Azure DevOps, or AWS CodePipeline.Monitoring & Logging: Tools like Prometheus, Grafana, or cloud-native monitoring solutions.Preferred qualifications include experience in the banking or financial services domain, knowledge of data privacy regulations, and exposure to generative AI or LLM fine-tuning.



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