Worked with google cloud platform, developed API which extracted sequential metrics data from GCP using python for vendors. Built Time-series machine learning and LSTM Recurrent Neural network model and deployed it in google cloud production environment. 
 
• Structured the metrics data using pandas, NumPy and created plotting graph, dashboards for vendors using matplotlib, seaborn. 
 
• OCR image processing using OpenCV library, tesseract and template matching for extracting invoice data from images. 
 
• Developed tool which converted the unstructured data to structured way for ML model and entity extraction using Spacy. 
 
 

 Developed machine learning models using algorithms like Random Forest, Logistic regression, SVM, KNN, Naïve Bayes etc for customers usages and sales predictions. 
 
• Developed customers segmentation model using unsupervised learning algorithms like K- means clustering, DBSCAN. • Developed data pipeline API using python Django which gets data from ERP system using pysftp, convert the data to json format, validate it against python Avro schema and copy the data to PostgreSQL database. 
 

Analysed data using pandas, NumPy and data visualization tools like Tableau. 
• Project Title : Apple Offshore. (Tata Consultancy Services March 2011 to July2012). 
• Experienced applying AI techniques (predictive analytics. optimization, semantic analysis, time-series analysis, advanced visualization) to real world problems. 
 
• Worked on developing statistical model/applications in Python language for multiple platforms. 
 
• Experienced in error and exceptional handling. • Experienced on manipulating and preparing large, heterogeneous data set to support advanced analytics. 
 
• Experience in designing the automation framework using Shell scripting. 
 
• Experienced in PS and Oracle database.

 Monitored and resolved the issues logged by the end users in the incident reporting tool (Apple supplied tool Espresso). • Automation using python and Unix shell scripting. • Set up software on production boxes. • Maintained records of daily transactions, problems and remedial actions taken and installation activities via ticketing tool. • Observe system functioning to verify correct operations and detect errors. Techniques have been developed to do a better diagnostic of the problems. • Operating System: Sun Solaris 10, Mac OS X (10.4 Tiger, 10.5 Leopard, 10.6 Snow Leopard, 10.7.2 Lion), Red Hat Linux. 
 
• Special Software: VMware, Puppet, Verdad, Cacti, Espresso