Experience

Nepal's largest private telecom had a problem: international call revenue was shrinking, and OTT apps like WhatsApp and Viber were winning. As a part of the Strategy & Planning unit, I got the opportunity to own it and come up with effective strategies to solve it. I dug into every ILD plan offered by every major operator across UAE, Qatar, Malaysia, Saudi Arabia, and India, then benchmarked them against what comparable migrant worker populations (Indian, Bangladeshi, Filipino) were getting in the same markets. The answer was clear: Nepali users were getting a worse deal. This turned them away from proper telecom channels to unauthorised use of OTT platforms. I turned that analysis into a board-level report with concrete recommendations on pricing, product redesign, and partnership renegotiation. It was presented directly to the C-suite and the board.

FlavorLens is a 10-person F&B intelligence startup sitting on 10M+ recipes, 100M+ menu items, and data from UberEats, DoorDash, Grubhub, and Google Maps. Reporting to the CEO, I was the connective tissue across product, marketing, and sales all at once. I managed the full data pipeline end-to-end, built the QC frameworks that made the data accurate enough to actually sell, and ran a team of 2–3 data engineers. On the commercial side, I developed and executed the company's first enterprise GTM plan and closed the first paying client. I also translated technical outputs into client-facing narratives and produced market intelligence reports used directly in sales pitches.

Daraz is Nepal's largest e-commerce marketplace, backed by Alibaba Group. I joined through their competitive Future Leadership Program and immediately got into the data. I led the Buyer 360 project, applying RFM segmentation and A/B testing across a 1M+ user base to figure out which campaigns were actually working and why. One outcome: shopping cart revisit rates climbed from 25% to 40% by combining CRM insights with smarter incentive design and regional coordination. I also automated the performance reporting pipeline, cutting the reporting cycle by 3–4 days, and built regression models to improve logistics profitability across 50%+ of shipping locations.

This was my first role out of university! And it threw me straight into the deep end of network performance data. I diagnosed voice and data quality issues across Ncell's coverage area, built a weekly diagnostic reporting cadence that went out to engineering and operations teams, and owned trouble tickets end-to-end for site rectification and transmission maintenance. The results were concrete: network coverage improvements across 80%+ of the coverage area, a 70% reduction in problematic sites, and transmission congestion cut from around 30% down to under 10%.