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