payforpain

1.Selected and optimized traffic segments between SSP and DSP platforms based on target parameters. 2. Analyzed segment performance post-integration to scale high-performing traffic or minimize low-performing sources. 3. Investigated root causes of revenue deviations to prevent drops and replicate successful growth patterns across segments. 4. Managed daily tasks, workload distribution, and traffic quality compliance metrics within the team. 5. Optimized multiple ad formats (push notifications, in-page push, pop-ups) to maximize conversion rates and campaign value. 6. Defined and prioritized product/feature tasks to consistently optimize internal operational platforms.

1. Monitored and verified widgets and SSP programmatic streams to eliminate fraud patterns. 2. Integrated newly acquired widgets and supply sources into the centralized Anti-Fraud Checker tool. 3. Reconciled variance and data discrepancies between internal Publisher and external DSP statistical systems.

1. Assisted in the creation, installation and removal of advertising widgets (Pop-Under, Push, Native, In Page) on websites. 2. Audited high-risk banking transactions to protect against payment fraud.

1. Creating algorithms and training methods to achieve business goals. 2. Keeping the deadline and working beyond limits to support the team. 3. Supervised, audited, and trained a cross-functional department containing 3 Junior QC Specialists and 12 Data Moderators. 4. Conducted precision manual software checks (including A/B and smoke testing methods) and updated internal process documentation.

1. Troubleshooted customer software issues dynamically using live chat, structured ticketing tools, and voice support channels. Maintained expertise across core team tracking tool environments (Salesforce, Confluence, Jira, Slack, LiveChat). 2. Delivered direct, advanced remote desktop technical support via TeamViewer and LogMeIn. 3. Managed escalation logs, refund resolutions, and technical asset presentations to clients.

1. Authored structured reference documentation utilized for parsing data sets designated for neural network training models. 2. Exceeded key production output benchmarks in qualitative data structuring, securing a promotion to supervisor.