Data Scientist
Omni Inclusive
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
• 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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