Susenthar Raj Jegadeesh Chandra Bose

Data-driven professional with 3 years of experience as an analyst in the Information Technology (IT) sector. Skilled in programming languages such as SQL, R, and Python, as well as data analytics, business intelligence, and visualization tools such as Microsoft Excel, Alteryx, ParseHub, Tableau, Google cloud Platform, Jira, Confluence, and Power BI. Managed testing environment and live environment databases through Oracle DB. Completed Google Data Analytics certification. Collaborated with Business analysts, data analysts, subject matter experts to develop test case scenarios that meet customer requests and deliver client-facing, time-sensitive projects. Monitored test performance, provided feedback for optimization, and led to a decrease in errors detected during user acceptance tests. Created and scrutinized technical design documentation, training manuals, and resources for technical guidance, and developed training manuals for new employees.

Quality Analyst                                                                                                                      Jul 2019 - Jun 2021

Tata Consultancy Services, Chennai, India 

• Tested various CRs and scenarios in all phases of the SDLC using tools like Soap UI, Oracle DB, HP ALM, and UFT to accelerate testing completion by 50%.
• Facilitated technical requirements gathering sessions with stakeholders to ensure delivery of high-quality products within timeline constraints, decreasing time-to-market by 10%.
• Collaborated with the internal team, client, business analyst, data analyst, IT and Business stakeholders to define & execute system testing plans and generated over 50 automated reports and dashboards.
• Delivered timely business intelligence data to stakeholders, resulting in 50% improved knowledge sharing. 
• Examined product requirements & established key performance indicators to measure success metrics and increased customer satisfaction by 15%.

ACADEMIC PROJECT EXPERIENCE 

Predictive analysis and visualization                                                                                   May 2022- Dec 2022

• Transformed 10+ customer data points to identify trends & opportunities and used predictive analytics models with a 90% accuracy rate to forecast future sales performance and drive strategic decisions for the company.
• Devised report using SQL and Tableau to visualize KPIs & draw actionable insights from data analysis, achieving a 40% efficiency gain.
• Performed exploratory data analysis & predictive analytics on customer engagement & retention metrics for data spanning 5 years to identify key performance indicators with a 90% accuracy rate. 

Data transformation and scrapping using Alteryx and ParseHub tool                           May 2022- Aug 2022

• Engineered Alteryx tool to extract and transform data from 15+ e-commerce websites, resulting in an 80% increase in accuracy of sales, marketing insights, trends, and customer behavior.
• Built analytical models utilizing a combination of blending, parsing, and transforming techniques to refine valuable insights from large datasets, achieving an 80% reduction in manual reporting efforts.
• Identified gaps and areas of improvement by analyzing 3 years of historical data for future analysis and product development initiatives, delivering a 15% higher ROI.

Data exploration and preparation                                                                                       May 2022- Aug 2022

• Interpreted 10,000+ rows of Netflix subscription data to identify trends & patterns in customer behaviour to assess customer ROI.
• Facilitated & deployed a decision tree model to analyze drug usage data and assess various parameters like age, sex, and symptoms, yielding accurate drug recommendations for 20+ illnesses.
• Applied apriori algorithm to analyze 100K+ transactions and discovered 50+ item sets sold together in a supermarket with an accuracy of 99%.

Data modelling and warehousing                                                                                          May 2022- Aug 2022

• Performed rigorous data cleaning & preparation activities on the network provider company records, improving accuracy by 75% using requirement analysis.
• Operated data acquisition, modelling, and requirement analysis for an airline company using Microsoft SQL Server to generate insights and successfully achieve a 10% reduction in churn rate.

Employed advanced SQL queries to join multiple tables and develop detailed reports and data warehouses in Microsoft Access to store over 500K records, increasing overall efficiency by 30%.