Machine Learning Expert
- Tata Consultancy
- 4 - 7 years
- Bengaluru
- 1 day ago
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Job Description
Technical Skills-
Programming Languages:
Expertise in Python and R for data analysis and algorithm development.
Familiarity with Java, C++, or Julia for system-level programming and optimization.
ML Frameworks & Libraries:
Proficiency in TensorFlow, PyTorch, Keras, Scikit-learn, and other ML libraries.
Hands-on experience with XGBoost, LightGBM, or CatBoost for boosting techniques.
Mathematical Foundations:
Strong understanding of linear algebra, calculus, probability, and statistics.
Data Processing:
Experience with tools like Pandas, NumPy, or Dask for handling and transforming datasets.
Knowledge of ETL (Extract, Transform, Load) processes.
Model Development:
Skills in designing, training, and fine-tuning machine learning models.
Expertise in hyperparameter tuning and cross-validation techniques.
Big Data Technologies:
Familiarity with Apache Spark, Hadoop, or Snowflake for processing large-scale datasets.
Cloud Platforms:
Proficiency with AWS SageMaker, Google AI Platform, or Azure Machine Learning for deploying and managing ML models.
Database Management:
Knowledge of SQL for structured data querying and NoSQL for unstructured data handling (e.g., MongoDB, Cassandra).
Version Control & Workflow:
Use of Git/GitHub for collaborative work and model version control.
Familiarity with Jupyter Notebooks or IDEs for experimentation.
Deployment:
Experience in deploying ML models using Docker and Kubernetes.
Knowledge of integrating models with APIs and CI/CD pipelines.
Must Have-
Strong Programming Skills: Proficiency in Python, R, Java, or C++ for implementing ML algorithms.
Mathematics and Statistics: Solid understanding of linear algebra, calculus, probability, and statistics.
Machine Learning Algorithms: Expertise in supervised, unsupervised, and reinforcement learning techniques.
Data Preprocessing: Ability to clean, preprocess, and transform raw data into usable formats.
Model Evaluation: Knowledge of metrics like accuracy, precision, recall, F1-score, and ROC-AUC for evaluating models.
Deep Learning: Familiarity with neural networks, CNNs, RNNs, and frameworks like TensorFlow or PyTorch.
Problem-Solving Skills: Analytical thinking to design and implement ML solutions for real-world problems.
Job Classification
Industry: IT Services & ConsultingFunctional Area / Department: IT & Information SecurityRole Category: IT SecurityRole: IT Security - OtherEmployement Type: Full timeContact Details:
Company: Tata ConsultancyLocation(s): Bengaluru
Keyskills: Machine Learning Ml Algorithms Python
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