Data Science with less than a year in Data Analysis, Time-Series Modeling, and Development Economics
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Results-oriented MSc Statistics and MBA Finance graduate with a strong research foundation in data analysis, time-series modelling, and development economics. Demonstrated experience applying statistical methods to real-world policy datasets including UNDP Human Development Index data and Government of India CPI series. Passionate about AI-enabled knowledge systems, digital learning, and evidence-based approaches to humanitarian, development, and peacebuilding challenges. Seeking to contribute analytical and knowledge management skills.
KTHM College, Nashik
M.Sc. in Statistics · Statistics
August 1, 2024 – June 30, 2026
YCMOU, Nashik
MBA in Finance · Finance
August 1, 2024 – June 30, 2026
R.B. Narayanrao Borawake College, Shrirampur
B.Sc. in Statistics · Statistics
August 1, 2021 – June 30, 2024
Study of Worldwide Human Development Indices
January 1, 2025 – June 1, 2026
Analysed HDI across 20 global countries and 35 Indian states using UNDP, World Bank, and UN DESA datasets. Applied Multiple Regression (R2 = 0.991 global, 0.978 Indian states), ANOVA, Cluster Analysis, and GDI analysis. Identified key structural drivers of human development gaps including gender, income, and education indices. Tools: R, Python, MS Excel directly aligned with UNDP's core knowledge frameworks.
Empirical Analysis of CPI Inflation Dynamics in India
January 1, 2025 – June 1, 2026
Conducted comprehensive time-series analysis of 6 CPI series (Rural/Urban/Combined Food & Fuel) from Jan 2011-Dec 2025 using NSO/MoSPI data. Applied Sequential ADF unit root testing, additive seasonal decomposition, Box-Jenkins SARIMA model identification and selection (AIC). Best-fit model SARIMA(1,2,2)(0,1,1)[12] for all food series; fuel forecast MAPE < 1% (highly accurate per Lewis 1982). Generated 6-month ahead CPI forecasts (Jan-Jun 2026) with 95% prediction intervals; policy recommendations submitted to guide. Tools: R, Python (statsmodels, pandas), MS Excel | Data: Government of India, NSO, MoSPI.
Statistical Study of Common Insurance Schemes in India
January 1, 2024 – December 31, 2024
Analysed policyholder data patterns, claim statistics, and risk coverage across public and private insurance sectors. Applied statistical tools including risk models and regression analysis to real-world economic data.
Cyber Security Course
YCMOU & Skills Factory Learning
March 1, 2026 – Present
Career Readiness Program
VHD Foundation, KTHM College
January 1, 2026 – Present
MEPSC Skill India Certificate
MEPSC Skill India
July 1, 2025 – Present
Introduction to Data Science and AI Tools Workshop
G-TEC Jain Education, Nashik
May 1, 2025 – Present
Cultural Fit Analysis
The candidate's academic projects demonstrate a strong interest in socio-economic data analysis, aligning with roles that require impact-driven research. The pursuit of both an M.Sc. in Statistics and an MBA in Finance indicates a broad intellectual curiosity and a desire to understand both the technical and business implications of data. The certifications, including a Cyber Security Course and a Career Readiness Program, suggest a proactive approach to skill development and professional growth. However, the lack of diverse project types (all academic) and professional experience limits the assessment of adaptability to varied organizational cultures.
Soft Skills & Operational Fit
The candidate's profile summary highlights a passion for AI-enabled knowledge systems and evidence-based approaches, suggesting a good operational fit for data-driven roles. The detailed project descriptions indicate strong analytical thinking and problem-solving skills. However, without direct work experience, the ability to collaborate in a professional team setting and handle project pressures is not explicitly demonstrated.