Navneet Govil

• Led the development of a machine learning algorithm to match job seekers with relevant job postings.
• Defined matching criteria based on skills, experience, and job requirements.
• Trained the algorithm on a large job seeker profiles and job postings dataset.
• Integrated the matching system into the platform, resulting in a 50% reduction in talent pipeline time and a 30% increase in product usage.
• Continuously monitored and optimized the system to improve accuracy and relevance.

• Led the selection and implementation of Sigma, a user-friendly BI tool aligned with business needs and technical requirements.
• Negotiated a 40% cost reduction with vendors, demonstrating financial acumen and ensuring a cost-effective solution.
• Empowered business users to analyze data independently, improving efficiency and decision-making.
• Developed a compelling business case for Sigma, securing executive buy-in and demonstrating strong leadership and communication skills.
• Successfully transitioned the organization to the new platform, minimizing disruptions and maximizing user adoption.

These APIs helped enterprise customers integrate their location-based business data with significant search engines in near real-time. The project proved its value during the 2020 pandemic when location-based businesses urgently needed to update their location data on internet platforms. I spearheaded the product lifecycle from concept to launch on these APIs.

Activities:

• Assessing product-market fit by understanding customer needs and product value proposition
• Building a product roadmap and collaborating with various stakeholders
• Defining product requirements and writing user stories
• Heading product development, working with engineers on design discussions, and performing user acceptance testing (UAT)
• Working with the marketing team in building marketing material, product positioning, and defining product pricing
• Leading client conversations on product demos for early adopters

• Led the implementation of a Generative AI (Gen-AI) solution powered by OpenAI.
• Developed and trained the AI model to configure client job feed integrations automatically and extract relevant job information from job postings like title, skills, education, certifications, location
• Ensured accurate job posting on the platform by automating data mapping, extraction, and formatting.
• Streamlined the onboarding process for new clients and improved platform reliability.
• Monitored and optimized the AI model for continued accuracy and efficiency.

Google Cloud Platform (GCP) is one of the world's top three cloud service providers. It is a crucial cloud vendor for any distributor to be successful in the cloud technology distribution industry.

The project involved:

• Defining the roadmap for the global distribution of GCP
• Aligning with senior executives on priorities
• Collaborating with regional managers to establish local relationships with Google and launching the product in that country
• Establishing KPIs and metrics to measure product usage and success
• Working with the engineering team explaining product requirements throughout the Agile cycle
• Collecting user feedback and interviewing customers for product improvement opportunities
• Announcing new feature releases and providing demos
• Enabling sales through knowledge transfer sessions, demos, and documentation.

These marketplace apps provided many more features/functionalities to the customers to help them solve their multi-cloud business use cases. This helped with an improved net promoter score (NPS), a better customer retention rate, and a new revenue source for the organization.

This project involved:

• Exploring various third-party vendors available in the market and accessing each for the available market opportunity
• Building a marketplace integration strategy/roadmap and prioritizing vendor integration
• Managing requirements and engineering discussions with the vendor for integration
• Collaborating with the marketing/customer success team for announcements and customer adoption of the apps
• Launching and measuring the success of the apps on the marketplace

• Partnered with organizational stakeholders to gather comprehensive requirements and align on the project's vision and goals.
• Facilitated discussions and workshops to define the scope and prioritize features for the MVP, balancing business needs and technical feasibility.
• Conducted thorough user research and testing to validate the MVP requirements, ensuring the solution addressed pain points and delivered a user-friendly experience.
• Documented detailed user stories, acceptance criteria, and wireframes to guide subsequent design and development efforts.

• Analyzed Google's end-to-end localization process, pinpointing key inefficiencies and pain points.
• Developed a streamlined process flow, incorporating optimized workflows and enhanced communication channels.
• Researched and recommended new tools and technologies to improve efficiency and accuracy while minimizing costs.
• Delivered actionable recommendations, including a roadmap for implementation, to drive significant improvements in Google's localization efforts.

• Text Kernel API Integration: Seamlessly integrated Text Kernel APIs to enhance talent data parsing, indexing, and search functionalities, resulting in improved talent discovery and a more user-friendly experience for recruiters.
• People Data Labs API Integration: Leveraged expertise in data pipeline management to integrate People Data Labs APIs, enabling efficient talent importation and enrichment of the platform's talent pool.
• Namsor API Integration: Ensured the successful integration of Namsor APIs for talent identity, upholding data integrity and building trust within the platform.

• Product Ownership: Served as the product owner, defining the product roadmap, writing detailed requirements, and aligning priorities with senior leadership to ensure the app met the needs of the commercial real estate mortgage industry.
• Cross-Functional Collaboration: Led a scrum team and collaborated with sales, senior management, engineers, design, operations, and support to deliver a high-quality product on time and within budget.
• Data-driven Enhancements: Implemented new features and UI changes based on extensive market research, user feedback sessions, and competitor analysis, resulting in a 20% increase in client satisfaction.
• User-centric Focus: Actively sought data, feedback, and new product developments to ensure the app remained user-friendly and addressed the evolving needs of the commercial real estate industry.