Cindu Jayachandar

• Worked for a Cosmetic brand client
• Identified the analytical requirements for the customer and the project
• Gathered, cleaned and organized data for use and created useful datasets for analysis
• Conducted extensive research on large amount of customer data using Python and Pyspark to extract insights
• Applied various ML techniques for customer segmentation

Python - Pyspark - Microsoft Azure - Databricks - Datalake- SQL

• POC on Vertex AI, GCP for CI/CD Pipelines
• Developed and Deployed ML model in Vertex AI with CI/CD pipelines
• Migrated use cases from workbench to GCP Platform

GCP - Python - Vertex AI – Auto ML- Custom model - Kubeflow Pipeline - BigQuery - SQL

• Applied various ML techniques for various business requirements
• Developed complex SQL queries to obtain data from the DB
• Managed and analyzed data to bring out insights
• Used statistical analysis and data visualization techniques to identify trends and patterns in data
• Used Python data science packages scikit-learn, pandas, and matplotlib to analyze and visualize large datasets
• Involved in developing a NLP corpus model, Classification model , Text Extraction Model, Speaker Diarization model
• Built Dashboards in Tableau to visualize the KPIs
• Collaborated with software engineers to deploy machine learning models using Flask

Python - EDA - SQL - Classification - NLP - Spacy - Predictive Analysis - Flask