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Key Responsibilities
Design, develop, and deploy machine learning and AI models to solve complex business problems
Build and optimize end-to-end ML pipelines, from data ingestion and feature engineering to model evaluation and deployment
Implement and fine-tune deep learning architectures such as CNNs, RNNs, and Transformer-based models
Perform statistical analysis, feature selection, and model validation using appropriate evaluation metrics
Work with large datasets using SQL for data extraction, transformation, and analysis
Collaborate with data engineers, software engineers, and product teams to integrate models into production systems
Apply software engineering best practices, including modular coding, version control, testing, and documentation
Monitor model performance and continuously improve accuracy, scalability, and reliability
Communicate insights, findings, and recommendations clearly to technical and non-technical stakeholders
Required Skills & Qualifications
5+ years of experience in data science, machine learning, or applied AI
Strong proficiency in Python and ML/DL libraries such as scikit-learn, TensorFlow, PyTorch
Hands-on experience with deep learning architectures (CNN, RNN, Transformers)
Solid understanding of statistical modeling, feature engineering, and evaluation metrics
Strong expertise in SQL for data manipulation and analysis
Experience with software engineering practices: Version control (Git)
Unit testing
Modular and maintainable code design
Excellent problem-solving, analytical, and communication skills
data science,machine learning,data ingestion,feature engineering,
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