Experienced Data Analyst for 2+ years in interpreting and analyzing data in the insurance industry. Skilled in SQL server, MS Excel, Python.
SKILLS & ABILITIES
Experience in SQL, MS Excel pivot tables, pivot charts, and macros.
Having knowledge on Statistics.
Managing huge amount of data in MongoDB.
Proficient with Microsoft Excel, Word, and PowerPoint.
Skilled in data cleansing, creating dashboards and data visualization with Tableau.
Experience in Catastrophe modeling tools like Risk Link, Risk Browser and GES(AIG).
Understanding Insurance, deductibles, limits, coinsurance, treaty, EP curve, mean losses, Standard deviation.
Experienced in analyzing large sets of data and focusing on details.
Good analytical and strong communication skills in both written and oral.
Able to work as part of a team or independently.
CAT MODELING ANALYST, 08/2016 TO 01/2019, AMERICAN INTERNATIONAL GROUP INC. (AIG), BENGALURU, INDIA
Received Employee Recognition Award for showing top quality in terms of deliverables in AIG Analytics and Services. The core responsibilities and contributions included:
Analyzing large volumes of data, finding out the patterns in the large data set, converting them in a proper format for calculating the potential insurance losses.
Analyzing the risk & potential losses caused by any type of natural calamities.
Use of MS Access, Advanced MS Excel concepts and SQL to fetch and organize the proper data by which to analyze the risk & losses.
Making the data understandable and presentable by using data visualization techniques.
Continuously keeping in touch with our clients to understand their requirements & delivering them within the timeline.
Mentoring juniors and new hires about technical concepts and job responsibilities.
Managing High Complexity Europe region Post-Bind as well as Pre-Quote account.
Christ University, Bangalore, India 
Master of Technology, Computer Science & Engineering [GPA : 3.22/4]
West Bengal University of Technology, India 
Bachelor of Technology, Computer Science & Engineering [GPA : 3.49/4]
“Social Media Analytics on Twitter content” (2016)
Collecting tweets using twitter API in python and stored in PostgreSQL database.
Cleansing the data through ETL process, performed Sentiment analysis with NLTK (Natural language tool kit) in python.
For better visualization, data were represented in OLAP cube with facts and dimension tables.
User interface for Project was in HTML5 and CSS.