SPANDAN BORKAR

Aspiring analyst with a proven ability to extract insights from complex datasets using SQL, Python, Excel, and Power BI, with 
strong foundations in ETL, data cleaning, transformation, and visualization. Delivered 60% efficiency gains through automated
reporting and KPI tracking. Adapt at building interactive dashboards, enabling data-driven decision making and collaboration 
across cross-functional teams in Agile environments.

PROFESSIONAL EXPERIENCE
IGT solutions September 2024 – February 2025
Process Analyst Intern
 Applied SERVQUAL model to evaluate inflight services, uncovering 3 key pain points affecting satisfaction scores.
 Conducted primary surveys of 1,500 passengers across multiple cities, collecting structured data on key
KPIs like seat comfort, entertainment, cleanliness, crew responsiveness, and food quality.
 Conducted structured interviews with 10 Air India staff and analyzed qualitative feedback using thematic coding 
techniques.
 Identified 3 key service pain points (inflight entertainment, cabin cleanliness, and food consistency) contributing to a 
20–30% drop in satisfaction scores.
 Delivered a roadmap of 6 strategic recommendations, including IFE upgrades, digital complaint tracking, 
and menu customization options that were acknowledged by internal management and integrated into 
the Agile planning cycle.
 Strengthened data-driven decision-making framework and contributed to enhanced customer experience 
benchmarking efforts.
RELEVANT PROJECTS
Retail Sales Dashboard (Superstore)
Tools: Excel, Power BI, DAX
 Developed a data model and interactive dashboard from 12,000+ records, revealing profit margin trends
and inventory misalignments, leading to a 15% inventory cost reduction.
 Used DAX to calculate key KPIs including Gross Margin %, YOY growth, and Product Performance Index.
Sales Forecasting with Time Series
Tools: Python, Power BI, Excel
 Forecasted monthly revenue trends enabling demand planning for a retail client via time-series modeling and 
ETL pipelines.
 Reduced stockouts by 18% and improved procurement decisions with visualization ofseasonal patterns.
Netflix Viewer Analytics
Tools: Power BI, Excel
 Analyzed 6,000+ titles using Power BI to reveal viewer trends, aiding a 25% projected retention boost.

MBA in Business Analytics