Sai Sankalp Singh Tuljaram

> Engaged in data ingestion initiatives that incorporate diverse card tokenisation methods, ensuring smooth data acquisition, streamlining data flow, and strengthening data security to improve business operations in the banking sector. > Guided a group of six professionals through the complete life cycle of banking projects, overseeing the process from development to successful implementation. > Engaged in 17 data ingestion projects aimed at resolving intricate business-related data challenges and successfully delivering projects within designated timelines. The ingestion processes is designed to seamlessly transfer bank data into a Hadoop system, facilitating efficient data retrieval without modifying the master database. Rigorous card tokenisation procedures are implemented to uphold data security standards.

Participated in a comprehensive 30-day training program focused on big data technologies such as Hadoop, Hive, Spark, and Scala, gained hands-on experience collaborating with industry experts to address intricate business-related big data challenges. Subsequently, transitioned to a role within a banking domain company contributing to their data ingestion and reporting projects.

> Contributed as a member of the design and development team for a mobile and web application with in the company, delivering security services to other businesses. > Engaged in front-end development of applications, utilizing my skills in HTML and Java Script >Additionally, served as a database handler for the company, responsible for maintaining database information and delivering requested data to facilitate informed business decisions. > LeveragedmypreviousexperienceinMachineLearningtoproposetheincorporationofachatbotinthe application. Utilising Natural Language Processing, the chatbot aims to comprehend users' basic queries about the company and generate automated responses.

> The internship predominantly emphasised attracting potential clients to the company by informing them about the services offered. Additionally, involved in making cold calls and scheduling business meetings to acquire new clients for the company. > Assumed responsibility for Exposys 'reach-out' program; successfully attained a 15% conversion rate, surpassing the average of 4%. This accomplishment was achieved by actively and empathetically advocating for preliminary level meetings with customers.

> Engaged in real-world machine learning projects alongside a cross-functional team, with a primary focus on understanding various machine learning algorithms. > Utilised insights acquired from an intensive machine learning course to tackle complex project challenges and introduce innovative solutions. > Mainly concentrated on extracting data and engineering features for a significant volume of data. Successfully concluded the assigned project, achieving a 93% accuracy rate, and visually represented the attained results. > Actively contributed to team discussions, sharing insights from coursework, and collaborating with peers to effectively solve problems.