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Senior Data Analysis with 9+ years in FP&A, Budgeting & Forecasting, and Performance Reporting.
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Finance and Data Analyst with 7+ years of experience across banking, internal audit, risk management, and financial analysis, with strong focus on FP&A, budgeting, forecasting, and performance reporting using Excel and Power BI.
Hochschule Fresenius, University of Applied Science
Certificate · International Business Management
August 1, 2024 – June 30, 2024
Jagannath International Management School
P.G.D.M · Finance and Marketing
August 1, 2013 – June 30, 2013
University of Delhi
Bachelor of Commerce · Commerce
August 1, 2010 – June 30, 2010
Deutsche Vermögensberatung (DVAG)
Financial Advisor - Trainee
May 1, 2025 – November 1, 2025
Germany
HDFC Bank Ltd
Internal Auditor
March 1, 2020 – September 1, 2022
India
HDFC Bank Ltd
Teller
November 1, 2014 – March 1, 2020
India
Ecom Express Pvt Ltd
Accountant
May 1, 2014 – October 1, 2014
India
Compensation & Job Market Analysis Dashboard
November 1, 2025 – November 1, 2025
Analysed 30,000+ job market records across companies, cities, job roles, experience levels, demand indicators, and remote work options to study salary trends and hiring dynamics in the Indian job ecosystem. Performed data cleaning, feature engineering, and aggregation using MySQL, including numeric experience mapping, role seniority classification, and performance optimization through indexing. Conducted exploratory data analysis in Python (Pandas, NumPy, Matplotlib) to examine salary distribution, experience-based progression, demand vs hiring saturation, and remote vs on-site compensation patterns. Designed an interactive Power BI dashboard with executive and deep-dive views, featuring KPI cards, bar charts, line charts, scatter plots, donut charts, and stacked visuals, enabling dynamic analysis by city, company, role, experience, seniority, and work mode. Built a machine learning salary prediction model (Random Forest Regressor) using engineered features, achieving an R2 score of ~0.53 and validating predictive performance using MAE. Delivered actionable insights on seniority-driven salary premiums, non-linear experience growth, demand saturation effects, and company-wise pay benchmarking, supporting workforce planning and career analysis.
Financial Time-Series Forecasting & Risk Analysis
October 1, 2025 – October 1, 2025
Analysed 30,000+ daily financial time-series records (~15 years) to study price trends, trading volume, volatility, returns, and momentum indicators using Python and Power BI. Performed data preprocessing, feature engineering, and exploratory analysis in Python (Pandas, NumPy, Matplotlib, Seaborn), including moving averages (SMA-20, SMA-50), daily return distributions, and volatility analysis. Built and evaluated a machine-learning forecasting model (Random Forest Regressor) to predict next-day closing prices, using time-aware train-test splits and performance metrics (MAE, RMSE). Designed an interactive Power BI dashboard with KPI cards, price trend lines, volume analysis, RSI momentum indicators, return distribution histograms, and dynamic slicers for time-based analysis. Delivered actionable insights on trend direction, volatility clustering, volume-price relationships, and overbought/oversold conditions, supporting data-driven financial analysis and risk assessment.
Sales & Profitability Performance Dashboard
September 1, 2025 – September 1, 2025
Analysed 8,500+ retail sales transactions using MySQL and Python to identify revenue trends, product performance, outlet efficiency, and customer purchasing patterns. Performed data cleaning and exploratory analysis in Python (Pandas, NumPy) and validated KPIs including Total Sales ($1.20M), Avg Sales, Item Count, and Ratings. Developed an interactive Power BI dashboard with KPI cards, donut charts, bar charts, trend lines, and slicers to visualize sales by item type, outlet size, and location tier. Generated actionable insights on low-fat product dominance, Tier-3 outlet performance, and medium-size store profitability, supporting data-driven retail strategy decisions.
Road Accident Analysis Dashboard
August 1, 2025 – August 1, 2025
Conducted in-depth analysis of 5,900+ road accident records to evaluate casualty severity, vehicle category involvement, road-type impact, and environmental conditions. Created interactive dashboards in both Excel and Power BI, utilizing Pivot Tables, Power Query, and DAX to build KPI cards, YoY comparisons, and multi-dimensional drilldowns. Visualized key insights including highest incidents on single carriageways, greater daytime casualties, and dominant involvement of cars and bikes supporting data-driven road safety decision-making.
Coffee Shop Sale Analysis Dashboard
July 1, 2025 – July 1, 2025
Analysed 149k+ sales transactions using SQL to identify MoM revenue trends, product demand patterns, and customer behaviour insights. Developed an interactive Power BI dashboard featuring calendar heatmaps, hourly demand trends, top products, and store-level performance metrics. Generated insights on peak selling periods and category profitability, supporting data-driven forecasting, inventory optimization, and strategic decision-making.
Bank Loan Performance Analysis Dashboard
June 1, 2025 – June 1, 2025
Analysed 38K+ bank loan applications using Advanced Excel to evaluate lending performance, portfolio quality, and borrower risk metrics across multiple dimensions. Built an interactive Excel dashboard with KPIs including Total Loan Applications, Funded Amount ($435M+), Amount Received ($473M+), Average Interest Rate, and Average DTI, along with MTD and MoM trend analysis. Performed Good Loan vs Bad Loan analysis, identifying that 86% of loans were healthy, and quantified funded and received amounts to assess credit risk and portfolio health. Created visual analyses for monthly trends, regional (state-wise) performance, loan term distribution, employment length, loan purpose, and home ownership, enabling data-driven lending and risk insights. Delivered actionable insights to support credit policy evaluation, risk monitoring, and strategic lending decisions using Excel formulas, pivot tables, slicers, and charts.
Financial Modelling
IMS Proschool
June 1, 2026 – Present
Excel Fundamental
Corporate Finance Institute
June 1, 2026 – Present
IBM Data Analytics with Excel and R
IBM
June 1, 2026 – Present
Excel Skill for Data Analytics and Visualization
Macquarie University
June 1, 2026 – Present
Microsoft Power BI Data Analyst
Microsoft
June 1, 2026 – Present
PL-300 certification: Microsoft Power BI Data Analyst
Udemy
June 1, 2026 – Present
Financial Modeling: Build a DCF Model
Udemy
June 1, 2026 – Present
Overview of Financials in SAP S/4HANA
SAP
June 1, 2026 – Present
Certificate of Korean Language Hobby Class
Korean Cultural Centre
June 1, 2026 – Present
The Complete Financial Analyst Course
Udemy
January 1, 2025 – Present
SQL – MYSQL Complete Master Bootcamp, Beginner-Expert
Udemy
January 1, 2024 – Present
Cultural Fit Analysis
The candidate's project diversity, ranging from financial time-series to road accident analysis, demonstrates adaptability and a broad interest in applying data analysis across different sectors. Their experience in an international setting (Deutsche Vermögensberatung) and pursuit of a certificate in International Business Management suggest an openness to diverse work environments and cultures. The target role of Senior Data Analysis aligns well with the candidate's demonstrated technical skills and project experience, particularly in financial data analysis and dashboard development. The breadth of certifications also indicates a proactive approach to continuous learning and skill development.
Soft Skills & Operational Fit
The candidate's resume highlights experience in detecting and resolving discrepancies, compiling audit findings, conveying complex concepts, and evaluating control mechanisms, which suggests strong analytical, problem-solving, and communication skills. Their background in banking and finance indicates an understanding of regulated environments and attention to detail, which are valuable for operational fit. The project descriptions also emphasize delivering actionable insights, indicating a results-oriented approach.