Varun Dabbiru

Spearheaded the design and development of AR Mirror products for fashion retail, enabling virtual apparel visualization, reducing customer trial time by 25%, and addressing 65% of in-store pain points through Scrum.

Directed a cross-functional team of three specialists (AR engineer, ML engineer, Python developer), aligning efforts directly with the founder to ensure product-market fit and strategic roadmap execution.

Conducted extensive executive interviews and primary market research, influencing 80% of the product roadmap by translating findings into actionable business solutions.

Delivered a functional prototype within 4 months (8 sprints) using Scrum, accelerating time-to-market by 25% and proactively resolving blockers during daily stand-ups.

Facilitated impactful brainstorming sessions, consolidating over 50 ideas into 20 actionable features through structured prioritization techniques like dot-voting and MoSCoW.

Managed the creation and launch of PwC's Learning Lab, generating £500K annual revenue, by coordinating engineering, design, and compliance teams to deliver an agile online tax learning platform.

Architected and implemented a scalable Azure-based e-commerce solution (Shop Digital), generating £600K annual revenue by leveraging Umbraco CMS, .NET Core, and ASP.NET Web API.

Enhanced e-commerce experience via API integrations (Companies House, Stripe), reducing form abandonment by 13% and increasing transaction completion rates by 30%.

Delivered Phase 2 of Global VAT Online for 8,000+ users, driving 30% user base growth with subscription-increasing features like tax newsletters and cross-country rate comparisons.

Optimized dynamic filtering layouts for the Working Capital platform through A/B testing, boosting engagement by 25% and reducing service turnaround times by 20%.

Managed development of an ML/AI-driven cognitive chatbot as Product Owner, increasing user satisfaction by 40% and reducing Level-2 escalations by 70% through cross-functional collaboration.

Implemented K-means clustering algorithms for SLA pattern recognition and automated delay flagging, leveraging historical data to optimize operational efficiency.

Streamlined identity management processes in the telecom sector, achieving a 20% reduction in system downtime through SAP integration and automated deletion of inactive IDs.

Ensured a 99% defect-free release of eWellness iON, a cloud-based healthcare product for SMBs, by leading QA testing and collaborating with project and test managers to eliminate testing gaps.

Improved inventory approval efficiency by 35% for SMB units through automation, reducing manual effort by introducing tiered workflow and leveraging existing APIs for auto-validation and approvals.

Facilitated requirement validations through regular and ad-hoc discussions, ensuring alignment and a streamlined QA process, resulting in a high-quality product that exceeded customer expectations and contributed to client base growth.