Product Data Operations PM at MSL FAIR, Meta

At Meta's FAIR team, I lead programs for autonomous AI agents—systems that can use computers and phones just like humans do bridging research, engineering, legal, and vendors to make ambitious AI research happen.

I manage a million-dollar vendor portfolio for data collection programs for agent training, delivering millions of training data points for models like Llama 4, and contribute to operational processes that helped our team scale.

Streamlined project coordination, contract management during pre-construction by implementing estimation workflows and stakeholder alignment strategies, effectively reducing scope creep and accelerating project kickoff timelines.

Improved cross-functional teamwork and project planning by using Agile methodology with SDLC & tools like JIRA, Scrum, & Procore. Managed sprints, change management, risk assessment, and scope control resulting in better communication, a 20% reduction in delivery delay and lower project risks in cloud migration & application deployment projects.

Overhauled authentication and access management systems by introducing OKTA, integrating secure SSO and session management (refresh token logic), which improved user experience, security, and operational performance for client-facing healthcare web applications.

Led business process improvement initiatives and automated onboarding workflows by leveraging AI, SQL, Python, and Azure-based solutions, enabling seamless, no-touch onboarding of 1,200+ hospitals, ensuring 100% HIPAA compliance, and driving a 4X growth in hospital onboarding and operational efficiency.

Developed interactive KPI dashboards using Power BI and PMO frameworks, improving forecasting accuracy and executive reporting, which led to a 25% increase in project predictability and stakeholder confidence.

Boosted project delivery efficiency by leading end-to-end management of a $6M portfolio for AI/ML data collection and annotation, implementing detailed roadmaps, project milestones, and KPI tracking for high-impact product lines like Oculus, Portal, and RayBan Smartglasses.

Enhanced cross-functional collaboration and team productivity by integrating Agile methodology with SDLC best practices, and utilising tools like Asana and Kanban for granular task breakdown, and working closely with global teams including engineering, product, and vendor partners resulting in accelerated delivery by 20% and better alignment with sprint goals.

Increased transparency and data-driven decision-making by designing systematic reporting frameworks using SQL, Python and automating budget tracking workflows with Azure Logic Apps, providing real-time insights for leadership on resource utilization and operational performance.

Accelerated project timelines and reduced supply chain and vendor-related costs by 25% through optimized resource management, risk mitigation protocols, and vendor alignment, supporting a network of 50+ international vendor resources.

Developed comprehensive project guidelines and documentation (including RFPs and SOWs), proactively managing dependencies and communicating progress, blockers, and risks to key stakeholders, resulting in improved project forecasting accuracy and stakeholder confidence.

Owned end-to-end project lifecycles for high-impact data analytics projects for Fortune 500 Pharma companies, through extensive market research, Python (Pandas, NumPy) modeling and advanced statistical techniques for data analysis, visualizing results to deliver actionable reports and strategic insights on sales force alignment and drug performance.

Built 15+ interactive dashboards in Power BI and Tableau, performing analysis using DAX, automating data workflows with Power Query, and streamlining datasets in Excel and SQL to track KPIs customized to client requirements, integrated with PostgreSQL for data manipulation resulting in 35% boost in data accuracy of insights & process efficiency.

Improved data workflows and analytics reliability by designing efficient ETL pipelines using Azure Data Factory & Alteryx, and managing databases with Azure SQL , which increased processing efficiency by 35% and reduced data processing time by 40%, resulting in more accurate and timely reporting.

Served as consultant to FP&A teams to improve financial data workflows by managing data in Azure SQL

Database, organizing information in Azure Data Lake Storage, building data pipelines with Azure Data Factory, and processing large datasets using Azure Databricks. This led to a 35% boost in efficiency and more accurate financial analysis for budgeting, forecasting, and strategic planning.

Improved system performance and scalability by analyzing SaaS workflows and optimizing Java and JavaScript components for the Payment and Billing application (serving 5 million+ users), resulting in a 25% reduction in load time and enhanced user experience across key modules.

Enhanced infrastructure efficiency and reliability by deploying and managing virtual machines with VMware vSphere/ESXi, resolving network latency issues through DNS optimization on Linux systems, and refining system administration protocols leading to a 30% faster resolution time and reduced hardware costs.

Implemented automated solutions and resilience protocols by streamlining user management with PowerShell for Active Directory, optimizing Windows Server configurations for security compliance, and executing a disaster recovery plan across SAN-based server infrastructure, achieving a 70% reduction in recovery time objectives (RTO) during failover testing.