Winnow is a reporting and analytically tool for banking domain which is running on historical transnational data since it is a banking domain solution Winnow was using Tableau and Cognos as its back-end tools. Have designed and implemented Back-end tools which is ready for reporting and analysis to replace Cognos and Tableau.

The main idea it to reduce the time as each report is running on trillions of data thus Cognos and Tableau was taking 5-10 minutes for executing.

The BirchStreet system is an e-procurement system for Hospitality industries and science the system is being used from 1998 so we had lot of data in data center and this data also contains some data that is not well classified and also we had lot of duplicate data not only in sense of textual duplicates there were also contextual duplicates so we need to implement some of the machine learning algorithm.

Roles & Responsibilities:

• Research & develop Machine Learning models for Text classification and Similarity match problems, in the areas of Application & Data

• Provided Technical Design specifications and production quality code on time to meet project mile stones

• Provide Technical Design for all implemented algorithms to address the problems and engage with algorithm proliferation activities.

• Research and develop deep learning algorithms.

• Research and develop state of the art techniques in the field of computer vision, ML and DL.

• Develop the next generation of automation tools for monitoring and measuring Data Quality, with associated user interfaces.

We had a requirement to design and implement Elastic search with some business logics.

Roles & Responsibilities:

• Work directed with the Customer Master Data group to setup and provide the recommendations for over 1 billion data for Hospitality Industry, provided architectural design for overall Core Search platform with ElasticSearch.

• Implemented the Core Search platform for ElasticSearch.

• Configured three data nodes, with two master nodes and one client/coordinator node to search cluster and split across different data regions to support high availability.

• Code and developed custom Elastic Search have APIs.

• Coded java based ES Queries and custom ES Queries with aggregations using REST API for searching and accessing data in ES Cluster, implemented advice regarding analyzers, filers, templates and ES mappings.

Established compatibility with the Legacy System to adapt and integrate ES as modern technology.

The emerging role is about a solution to the core issues of customer portfolio development, retention and expansion. Customer Success is an integration of functions and activities of Marketing, Sales, Professional Services, Training and Support into a new profession to meet the needs of recurring revenue model companies as Multi-tenant. There are three necessary building blocks for this emerging profession: an in-depth knowledge of the customers, effective knowledge of the product being sold, and extensive domain expertise.

Roles & Responsibilities:

• Used a micro service architecture, with Python - based services interacting through REST Web services. Deployed services to Amazon Cloud Platform,

• Design and developed Securities with SAML2 and LDAP.

• Design Architect for major modules.