Data Science Manager
CurrentSpearheaded a team of 9 data scientists and engineers with which have conceived a Multi Touch Attribution product from scratch launched as a cloud agnostic licensed product.Using AI and Data Science technology in the corporate world to overcome complex business challenges. A dedicated effort to contribute with excitement and differentiated innovation to our clients in order to demonstrate value and benefits. Among the contributions are advances in Predictive Analytics, Machine Learning, Deep Learning, Natural Language Processing and Computer Vision.Areas around Data and AI: - KPI driven approach- Machine Learning E2E pipeline using "collect" - "transform" - "analyze" - "monitor" strategy- ML explainability using LIME, SHAP- Extensive usage of GitHub,R, Python, CI/CD pipelines in MLOps for faster path to production using Docker, Kubernetes, Microservices-Usage of supervised learning techniques like Random forest/Ensemble Logistic Regression/Ridge and lasso regression/Time series forecasting/SVM/XGboost/Adabost and unsupervised algorithms like RNN/LSTM to solve pratical business problems.