Cupertino, California, United States
• Designed, developed, and deployed an iOS app connecting influencers to eventgoers under a $50,000 contract for high-growth startup • Developed approximately 65% of functionality including payments, encryption, synchronization, and a transactional database system. • Led team of 6 developers to deliver over 120 app features by enforcing AGILE development sprints, increasing sprint velocity by 70% • Consulted CEO on GTM strategy. Designed UX tests for critical features. Identified & executed upsell opportunity for second app
Founded a profitable peer-to-peer storage network, attracting XXX bookings and $XX,000 in revenue. Closed for business due to COVID. • Launched 5 platforms & services by leading a team of 3 developers through hi-fidelity mock-ups & AGILE development sprints. • Developed competitive pricing strategy — sourcing data from 200+ storage facility sites • Secured $10,000 from Arrow Capital. Developed industry reports, unit economics, competitive intelligence, product & GTM strategy. • Led IP protection, liability coverage, marketing STP, and pricing models. • Created API for Boxlet, enabling cross-platform functionality between iOS, Android, and web users
• Recommended 5-year core product roadmap bringing in $25mn/year by conducting sentiment analysis; After analyzing over 700 escalations and bucketing customer needs into top 8 themes, prioritized most pressing features with customer survey, 200+ responses • Led team of 3 engineers to query 11 key usage metrics from customer database; Utilized metrics to design 3 user experiences, define and design 2 UI components, identify 2 critical product needs surfaced by 60+ customer workarounds, and rank feature importance • Coordinated product teams to architect the beta release of an accounting ledger anomaly detection AI by defining its 8 subprocesses
• Increased average call connect rate of 38 telemarketers from 5% to 12% by developing OpptyCall, a descriptive & prescriptive artificial intelligence that customizes telemarketer calling schedules based on their industry microvertical, geographic region, and horizontal • Reduced lead prospecting costs by $150K and improved lead quality by 23% by building a lead-qualification machine learning model • Increased opportunity production by 167% by (1) identifying lead-scoring changes that incorrectly prioritized leads, (2) identifying underperforming PPL vendors by vertical, (3) proposing telemarketer hiring schedules based on attrition and productivity curves • Reduced report generation time by 94% by writing Python scripts to generate and reveal insights at the campaign level on CPC ads