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Data Science with less than a year in Data Analysis & Business Intelligence
Final-year MSc Data Science student with strong proficiency in SQL, Python (Pandas, NumPy), Excel, Power BI. Skilled in data cleaning, data processing, statistical analysis, and generating actionable insights through reporting and ad hoc analysis. Experienced in Business Intelligence and MIS reporting with the ability to build dashboards and communicate findings clearly to stakeholders. A collaborative team player with strong cross-functional communication, analytical thinking, adaptability, and a curiosity-driven approach to solving real-world business problems.
Kristu Jayanti University
Master of Science · Data Science
August 1, 2024 – June 30, 2026
Kristu Jayanti College Autonomous
Bachelor of Computer Applications · BCA
August 1, 2021 – June 30, 2024
IPSR solutions ltd
Intern
June 1, 2025 – July 1, 2025
India
Interpe
Web Development Intern
July 1, 2023 – September 1, 2023
India
OLA Ride Booking Analysis
June 21, 2026 – Present
Diagnosed a 28.08% cancellation rate across 63,246 bookings, identifying driver-side cancellations (17.94%) as the primary revenue leak nearly double the customer cancellation rate. Uncovered that 55.5% of customer cancellations were caused by driver behaviour (not moving to pickup + asking to cancel), directly recommending a driver penalty and auto-cancellation system. Identified "Personal & Car related issues" driving 35.42% of driver cancellations, flagging fleet reliability as a critical operational gap requiring a maintenance program.
View ProjectCodeX Energy Drink - Market Analysis & Insights Report
June 21, 2026 – Present
Diagnosed a 9.8% brand awareness gap across 10 cities isolating reputation (not product quality) as the core acquisition barrier and segmenting 10,000+ survey responses to reveal 70% of demand concentrated in the 15-30 male demographic, directly shaping a targeted influencer and paid digital strategy. Proved online ads delivered the highest ROI by reaching 3,373+ youth respondents surpassing all other channels combined while flagging that neutral and negative sentiment dominated perception across most cities, elevating localized campaigns from optional to urgent business priority. Engineered a city-specific pricing architecture (₹50-99 across 7 cities, up to 150 in 3 premium markets) calibrated to local willingness-to-pay, protecting revenue without sacrificing volume.
View ProjectRetail Customer Behavior Analysis
June 21, 2026 – Present
Identified 80% loyal customers but only 27% subscribed, pinpointing 2,518 repeat buyers as the highest ROI conversion opportunity for the subscription program. Diagnosed 50% discount dependency on top products, flagging blanket discounting as the primary margin risk and redirecting strategy toward price-sensitive segments only. Revealed males drive 67.74% of total revenue vs females at 32.26%, exposing females as an underserved segment with direct campaign potential.
View ProjectGoogle Data Analytics Professional Certificate
Coursera
June 1, 2026 – Present
Data Science and Machine Learning
Future Skills Prime
June 1, 2026 – Present
Power BI for Beginners
Simplilearn
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity (ride-booking, market analysis, retail behavior) and involvement in academic societies (Data Bridge Society) suggest a proactive and collaborative mindset. Their interest in bridging the academia-industry gap and fostering data-driven innovation aligns well with a culture that values continuous learning and practical application. However, the experience is primarily academic and internship-based, which might require adaptation to a fast-paced corporate environment.
Soft Skills & Operational Fit
The candidate demonstrates strong analytical thinking, adaptability, and a curiosity-driven approach to problem-solving, as evidenced by project descriptions and self-summary. Their involvement in organizing tech talks and workshops suggests leadership and communication skills. The projects highlight an ability to translate data into business recommendations, which is crucial for operational fit in a data science role. However, the experience level is entry-level, which might require more guidance in a senior role.