Ushoshi Bose

MBA graduate in Business Analytics

Indore, India

Profile Score

About

MBA graduate in Business Analytics with 3+ years of experience in data analysis, KPI tracking, process improvement, and operational reporting across healthcare and telecom industries. Holds a published research paper and McKinsey Forward Program certification, with expertise in Python, SQL, Power BI, and Advanced Excel. Demonstrated ability to build end-to-end analytical solutions — from predictive models and financial forecasting to BI dashboards — across multiple domains and datasets. Adept at exploratory data analysis, dashboard development, and financial modelling — delivering insights that support strategic business decisions.

Skills & Expertise (27)

Advanced Excel Advanced

7.8/10

Years Exp

Python Intermediate

7.3/10

Years Exp

Pandas Intermediate

7.0/10

Years Exp

NumPy Intermediate

6.8/10

Years Exp

Power BI Intermediate

6.5/10

Years Exp

SOP Development Risk Analysis Trend Analysis Logistic Regression Audit Checks Data Reconciliation SQL MS PowerPoint MS Word MS Excel Industry Trend Evaluation Annual Report Analysis secondary research Risk Identification Profitability Evaluation Cost Evaluation Income Statement Analysis Pivot Tables Sensitivity analysis Scenario analysis Budget Forecasting Financial Modeling

Work Experience

Senior Executive

TaskUs India Pvt. Ltd.

Jul 2022 - Aug 2023

Conducted trend and risk analysis on 2,000+ delivery records using Excel, identifying 5 key operational bottlenecks impacting service quality. Tracked operational KPIs via Excel dashboards, enabling proactive identification of performance gaps across delivery workflows.

Business Analyst Intern

Practo

Aug 2024 - Oct 2024

Built a customer-response classification model (AUC 0.69) and quantified the ROI of targeted campaigns to optimize marketing spend and conversion efficiency.

Teammate – Client Support / Operations Analytics

VOIS India

Aug 2020 - Jul 2022

Cleaned and validated 50K+ healthcare records using Python (Pandas, NumPy), reducing missing entries by ~20%. Analyzed demographic and behavioral variables across patient data, identifying 4 high-impact factors influencing health outcomes. Built a Logistic Regression classification model to predict heart disease risk, achieving an AUC of 0.82.