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AI Summary
The role involves designing and implementing end-to-end ML and Deep Learning pipelines for regression and industrial control use cases. Responsibilities include optimizing neural network architectures and collaborating with cross-functional teams to integrate solutions into production.
Hiring: Data Scientist
Experience: 5+ Years
Experience: 5+ Years
We are looking for a highly skilled Data Scientist with strong expertise in Machine Learning, Deep Learning, and production-grade ML systems to solve complex real-world business challenges.
Key Responsibilities:
- Train and optimize Deep Neural Network architectures for Regression and Industrial Control use cases
- Design and implement end-to-end Machine Learning and Deep Learning pipelines including data ingestion, data cleaning, feature engineering, model training, deployment, and monitoring
- Work with large and complex datasets for preprocessing, exploratory data analysis (EDA), and feature engineering
- Apply Regression Models and Predictive Analytics to solve business problems
- Develop Time Series and Forecasting models for trend prediction and risk estimation
- Collaborate with cross-functional teams to integrate ML solutions into production environments
Must Have Skills:
- Deep Learning (Neural Networks, CNN, RNN, LSTM, Transformers)
- PyTorch, TensorFlow, Keras
- Python Programming
- Scikit-learn
- Pandas and NumPy
- Machine Learning (Regression, Classification, Ensemble Models)
- Time Series Forecasting and Predictive Modeling
- Model Training, Hyperparameter Tuning, and Cross Validation
Good to Have:
- Cloud Platforms: AWS, Azure, or GCP
- MLOps Tools: Docker, Kubernetes, MLflow, Seldon, etc.
- Exposure to Big Data and Data Engineering
- Experience with NLP, GenAI, or LLMs
Location : Remote
Note- Please apply via our official careers portal only, as applications sent directly to executives may not be considered.
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