Senior Data Scientist

The Senior Data Scientist role focuses on Data Engineering, Workflow Orchestration, and MLOps. Responsibilities include working with cloud platforms like GCP, AWS, and Azure, utilizing orchestration tools such as Kubernetes, and deployment tools like Spinnaker and Helm Charts. The role requires expertise in data processing with Apache Spark/Beam, workflow orchestration with Google Cloud Composer/Airflow, and MLOps practices including model deployment, monitoring, versioning, experiment tracking, and implementing CI/CD pipelines for machine learning models.

Must Have

• Experience with Google Cloud Platform (GCP), AWS, or Microsoft Azure.
• Proficiency in Kubernetes for orchestration.
• Experience with Spinnaker or Helm Charts for deployment.
• Knowledge of Apache Spark or Apache Beam for data pipelines.
• Familiarity with Google Cloud Composer or Airflow for workflow orchestration.
• Experience with MLOps tools like TensorFlow, Serving TorchServe, MLflow, DVC, or TFX.
• Ability to implement CI/CD pipelines specifically for machine learning models.
• Understanding of distributed training, resource scaling, and automated model retraining.
• Experience with DevOps and CI/CD tools like GitHub Actions or TeamCity.

Senior Data Scientist

Job Req Id: 1414477

Data Engineering & Workflow Orchestration

Cloud Orchestration Platforms Storage

• Experience with one of the Below Cloud Platforms Platform Orchestrators Deployment Tools
• Cloud Providers Google Cloud Platform GCP AWS Microsoft Azure
• Orchestration Kubernetes
• Deployment Spinnaker Helm Charts

Data Engineering Technologies Workflow Orchestrations

• Experience with one of the Below Data Engineering Technologies and Workflow Orchestrators
• Data Pipelines Processing Apache Spark Apache Beam
• Workflow Orchestration Google Cloud Composer Airflow
• MLOps Machine Learning Operations

• Model Deployment Monitoring. Experience with deploying machine learning models using tools like TensorFlow, Serving TorchServe or MLflow
• Model Versioning Experiment Tracking Proficiency in using tools like MLflow, DVC or TFX for managing model versions and experiments
• Continuous Integration for ML Implementing CICD pipelines specifically for machine learning models automating training deployment and monitoring workflows
• Scalability Resource Management Understanding of distributed training resource scaling and automated model retraining
• DevOps CICD
• CICD Tools GitHub Actions or TeamCity

Min Salary:

Max Salary: