Kolkata, West Bengal, India
Information Technology
Full-Time
Virtusa
Overview
WorkMode :Hybrid
Work Location : Chennai / Hyderabad /
Work Timing : 2 PM to 11 PM
Primary : Data Scientist
We are seeking a skilled Data Scientist with strong expertise in Python programming and Amazon SageMaker to join our data team. The ideal candidate will have a solid foundation in machine learning, data analysis, and cloud-based model deployment. You will work closely with cross-functional teams to build, deploy, and optimize predictive models and data-driven solutions at scale.
Bachelors or Master's degree in Computer Science, Data Science, Statistics, or a related field.
12+ years of experience in data science or machine learning roles.
Proficiency in Python and popular ML libraries (e.g., scikit-learn, pandas, NumPy).
Hands-on experience with Amazon SageMaker for model training, tuning, and deployment.
Strong understanding of supervised and unsupervised learning techniques.
Experience working with large datasets and cloud platforms (AWS preferred).
Excellent problem-solving and communication skills.
Experience with AWS services beyond SageMaker (e.g., S3, Lambda, Step Functions).
Familiarity with deep learning frameworks like TensorFlow or PyTorch.
Exposure to MLOps practices and tools (e.g., CI/CD for ML, MLflow, Kubeflow).
Knowledge of version control (e.g., Git) and agile development practices.
Work Location : Chennai / Hyderabad /
Work Timing : 2 PM to 11 PM
Primary : Data Scientist
We are seeking a skilled Data Scientist with strong expertise in Python programming and Amazon SageMaker to join our data team. The ideal candidate will have a solid foundation in machine learning, data analysis, and cloud-based model deployment. You will work closely with cross-functional teams to build, deploy, and optimize predictive models and data-driven solutions at scale.
Bachelors or Master's degree in Computer Science, Data Science, Statistics, or a related field.
12+ years of experience in data science or machine learning roles.
Proficiency in Python and popular ML libraries (e.g., scikit-learn, pandas, NumPy).
Hands-on experience with Amazon SageMaker for model training, tuning, and deployment.
Strong understanding of supervised and unsupervised learning techniques.
Experience working with large datasets and cloud platforms (AWS preferred).
Excellent problem-solving and communication skills.
Experience with AWS services beyond SageMaker (e.g., S3, Lambda, Step Functions).
Familiarity with deep learning frameworks like TensorFlow or PyTorch.
Exposure to MLOps practices and tools (e.g., CI/CD for ML, MLflow, Kubeflow).
Knowledge of version control (e.g., Git) and agile development practices.
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