Shreejit P.
Research Analyst @ IMF | Office of Risk Management
- Role
- Research Analyst at International Monetary Fund
- Location
- Washington, DC, US
- LinkedIn followers
- 500 followers
About Shreejit P.
As a Data Science student, I am passionate about unraveling the stories hidden in data and using ML/Statistics to make informed decisions. I have developed proficiency in R, Python, SQL, C++, and other relevant software and programs, enabling me to navigate the intricate realms of data analysis, visualization, algorithms, and database management. My goal is to become a data scientist who can create impactful solutions for real-world problems, especially in the areas of infrastructure, technology and business. I am eager to learn from and collaborate with experts and mentors in the field, and to contribute to the advancement of data science knowledge and practice. I am a dedicated, growth-minded, and curious data scientist who values diversity, creativity, and excellence.
Experience
Research Analyst
Jun 2024 — Present · Washington, DC, US
Built an automated dashboard to assess Capacity-to-Repay (CtR) risk by integrating time series forecasting, percentile-based benchmarking, and predictive modeling using historical outstanding Fund credit, GIR, exports, government revenue, and debt service for the Fund\'s financial accounts (GRA/PRGT/RST), and implemented dynamic data visualizations to project credit outstanding and quantify credit risk.• Monthly Data collection, aggregation, and data management for the Financial Risk Indicators Report (FRIR) and dashboard preparation. Create and maintain interactive dashboards to visualize financial risk indicators.• Designed and managed an SQL Server database (SSMS) for Financial and Non-Financial Key Risk Indicators (KRIs), facilitating monthly and quarterly reporting, improving data accessibility for Annual Risk Reports, and performing data cleaning, aggregation, and maintenance to uphold data integrity.• Assessed the Analytical Accuracy KRI by measuring the forecast performance of the IMF\'s World Economic Outlook (WEO) historical predictions comparing root mean square errors with predictions generated using ML algorithms such as RandomForest, SuperLearner, RNN etc, and reported to the board on the potential advantages of utilizing machine learning algorithms.
Education
Rato Bangala School
High School Diploma
2019 — 2021
Clarkson University
Bachelor's degree
2021 — 2024
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