- Lead development of advanced machine learning and statistical models
- Design scalable data pipelines using PySpark
- Perform data transformation and exploratory analysis using Pandas, Numpy and SQL
- Build, train and fine tune machine learning and deep learning models using TensorFlow and PyTorch
- Mentor junior engineers and lead code reviews, best practices and documentation
- Designing and implementing big data, streaming AI/ML training and prediction pipelines
- Translate complex business problems into data driven solutions
- Promote best practices in data science, and model governance
- Use tools like Python, TensorFlow, PyTorch, SQL, and cloud platforms
- Stay ahead with evolving technologies and guide strategic data initiative
Requirements
- Bachelor and/or Masters degree in either one of the disciplines: Computer Science, Statistics, Data Science, Data Analytics, Machine Learning
- Python, PySpark, SQL
- Pandas, Numpy, Excel, Plotly, Matplotlib, Seaborn, ETL, AWS and SageMaker
- Supervised learning models: Regression, Classification
- Unsupervised learning models: Anomaly detection, clustering
- Deep Learning Autoencoders, CNN, RNN, LSTM, hybrid models
- Model evaluation, cross validation, hyper parameters tuning
- Scikit-Learn, TensorFlow, PyTorch
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