Ing. Jaydeepkumar Gondaliya

Led a team of data scientists and engineers to improve the company's and contact database with ML, boosting data accuracy and coverage by ~30%. Owned end-to-end lifecycle for AI Go-to-Market features (enrichment & alerts), reducing sales outreach by 25% and lifting conversion rates by ~18%. Drove product adoption and customer success by defining clear rollout strategies, training sales teams, and monitoring KPIs, leading to a 20% increase in active user engagement within the first 6 months of launch.

Led a team of data scientists, engineers, and a designer to design, develop, and launch an AI-powered supplier search platform, resulting in a reduction of 40% in manual search time Conducted market research and analyzed the feedback of 30+ customers, which helped to improve the user experience of the product and to increase customer satisfaction by 70% Collaborated with the Data Product team to launch the MVP of the AI-based data enrichment system internally, resulting in reduced enrichment cost by 55%

Overhauled the obsolete legacy source code of a production application, resulting in increased usability and reduced run time performance by 50% Partnered with an external organization for data annotation and developed a training dataset for an AI model Collaborated with Data Scientists and developed an Auto-enrichment AI model, resulting in 50% reduced manual work Worked closely with the product team to assess the system outcomes and prioritize supplier data points to be auto-enriched

Collected, cleaned, and analyzed the supplier data using Python, SQL, and Excel to help the customer support and sales team showcase the sourcing project values to 20+ customers Collaborated with product managers and designers to analyze the product usage data and generate insights for further product development Partnered with cross-functional teams to analyze customer data and increased the daily active users by 10%, enhancing the user experience

Master Thesis topic: Webpage Classification using various Machine Learning and Deep Learning Algorithms.

Data Management, Transaction Management, Information retrieval/recommendation

Artificial Intelligence , Distributed Data Management , Data Management for Engineering Application

Digital Communication , Mobile Communication