14+ years of experience in predictive modelling, in Software Development , Data science (Machine Learning, Deep Learning ) and analysis within Fintech, Retail ,CPG, BFSI and Oil & Gas Believe in Design Thinking to move forward in an agile manner and when in doubt i revert to First principles While working as a Full Stack Data Scientist , my essential mandate is to leverage data science to improve efficiency and effectiveness across functions thus allowing managers to make analytics driven decisions across areas My role usually requires me to work closely with senior management , product managers and stakeholders across functions and verticals to understand requirements, identify the analytical problem and further develop and execute the requisite approach. My areas of expertise include: - Building relationships with a wide range of stakeholders and managing team of data scientists & analysts - Ability to manage change and to provide thought leadership in the area of analytics - Summarizing insights and delivering presentations to various stakeholders - Design, development, implementation and feedback generation for Projects - Managing the end-to-end delivery of projects - Hands of experience in analytical tools and languages (R/Python/SAS) - Machine learning as a service deployment using Azure DevOps Worked on Linear and Logistic regression, Clustering techniques like K Means, Hierarchical and Classification, SVM, Boosting, Random forests, Multinomial. - Experience in machine learning, supervised and unsupervised: Regression (Linear, Logistic, Ridge, LASSO, Elastic Net), Classification, Decision Trees (CART, CHAID), Random Forest, Neural Networks, , Clustering (K-means, hierarchical clustering, GMM, DBSCAN), Random Forest, Gradient Boosting , Dimensionality reduction (PCA, t-SNE) ,SVM,Sentiment Analysis, - Generative Models: LLM, Prompt Engineering , PEFT, Coding - Python , R and SAS , C#, JavaScript - Experience with big data platforms – Hadoop (Hive, Map Reduce), Google Cloud Platform – Big Query - Experience with Teradata, SQL and relational databases, also familiar with Tableau and R-shiny Deep Learning: Computer Vision - Transfer Learning using PyTorch and Keras frameworks NLP - Semantic Similarity, Pre Trained Hugging Face models, Topic Modelling etc. ML Deployment: Azure Ml, Azure Dev Ops, CI/CD Pipeline, GCP Version Management – Git, Project Management – JIRA, Documentation - Confluence Microservice Framework – Flask, Shiny, FastAPI Development Tools – Jupyter, RStudio, Azure Databricks , Postman, Spyder