Apr 2024 – Mar 2025 · 11 mos

• Driving AI-powered innovation to optimize Zycus’s product suite. Notable achievements:
• Contract Management: Boosted compliance by 25% and cut admin overhead by 30% using GenAI.
• Procurement Optimization: Achieved 20% cost savings through predictive analytics.
• Presales Automation: Reduced RFP response time by 40% and improved collaboration by 35%.
• Development Efficiency: Enhanced development speed by 50% with a virtual tool.
• Process Automation: Streamlined COE processes, cutting redundancy by 45% and improving test coverage by 60%.

Jul 2022 – Apr 2024 · 1 yr 9 mos

• Leading cross-functional teams to design and deploy AI-driven solutions that deliver measurable business value. Key achievements:
• AI Solution Development: Spearheaded the creation of AI products aligned with strategic goals and customer needs.
• Cross-Functional Leadership: Managed interdisciplinary teams, accelerating development cycles and fostering collaboration.
• Market Strategy: Guided AI product direction through in-depth market analysis and trend identification.
• Customer-Centric Innovation: Developed AI solutions tailored to customer pain points, boosting satisfaction and adoption.
• Product Lifecycle Management: Oversaw the product lifecycle from ideation to launch, ensuring continuous improvement.

Jul 2021 – Jul 2022 · 1 yr

• Led AI-driven projects, including a payment terms recommendation bot with 96% top-1 accuracy and a contract discovery bot that boosted retrieval accuracy by 40%. Enhanced supplier recommendation engine, improving matching accuracy by 30%. Managed a team to deliver cutting-edge data science solutions that optimized business processes.

May 2020 – Jul 2021 · 1 yr 2 mos

• Engineered a supplier recommendation engine that achieved 90% accuracy in top-1 recommendations and 99% in top-3, significantly enhancing procurement processes. Improved the engine's matching accuracy by 30% through innovative hashing-based techniques. Played a critical role in developing AI solutions that streamlined business operations and boosted efficiency.

Jul 2018 – May 2020 · 1 yr 10 mos · Bengaluru, Karnataka, India · On-site

• Built a propensity model for the sales team of a fortune 10 technology giant to predict the likelihood of an opportunity to convert at an early sales stage by analyzing customer profiles, customer business history with the client, and sentiment of the customer. Leveraged a hypothesis-driven approach to identify the significant features affecting the opportunity to win. Enabled the sales team of a fortune 10 technology giant to prioritize leads based on multiple factors which were fed into various classification algorithms attaining model accuracy of 78% resulting in cost savings of ~$80M
• Worked with the data science team to analyze customers' feedback and segregating them into five categories. Identified the key areas in these categories where there was a need for improvement resulting in improved customer satisfaction score by 7%
• Created predefined product packages based on customers' historical requirements and developed a recommendation engine that will offer these packages based on the description provided by the customer reducing a significant amount of manual effort