Posted:9 hours ago|
Platform:
Work from Office
Full Time
Expertise in Python and R for data analysis and algorithm development.
Familiarity with Java, C++, or Julia for system-level programming and optimization.
Proficiency in TensorFlow, PyTorch, Keras, Scikit-learn, and other ML libraries.
Hands-on experience with XGBoost, LightGBM, or CatBoost for boosting techniques.
Strong understanding of linear algebra, calculus, probability, and statistics.
Experience with tools like Pandas, NumPy, or Dask for handling and transforming datasets.
Knowledge of ETL (Extract, Transform, Load) processes.
Skills in designing, training, and fine-tuning machine learning models.
Expertise in hyperparameter tuning and cross-validation techniques.
Familiarity with Apache Spark, Hadoop, or Snowflake for processing large-scale datasets.
Proficiency with AWS SageMaker, Google AI Platform, or Azure Machine Learning for deploying and managing ML models.
Knowledge of SQL for structured data querying and NoSQL for unstructured data handling (e.g., MongoDB, Cassandra).
Use of Git/GitHub for collaborative work and model version control.
Familiarity with Jupyter Notebooks or IDEs for experimentation.
Experience in deploying ML models using Docker and Kubernetes.
Knowledge of integrating models with APIs and CI/CD pipelines.
Tata Consultancy Services
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