Shashvat Suhane

Intelligence TV( Formerly TVI )

Spearheaded the development of TV Intelligence tool that seamlessly integrates Linear, OTT & YouTube planning and optimization campaigns, facilitating enhanced client pitches, competitive analysis, and streamlined activation strategies for targeting & retargeting. Leveraging panel data and statistical methodologies, the solution delivered a remarkable revenue boost of $2.1M for the fiscal year 2023-24

• Expanded solution to a new regions like Australia, Canada, UK with distinct datasets, resulting in a significant revenue contribution of approximately $2.1 million.
• Worked on production level pipeline(pyspark) for faster deployment
• Performed unit testing on different metrics like Impressions, CPM, Reach, Frequency and documentation of new developed functionality and changes.
• Maintained code version changes in Bitbucket repo

Audience Mode( Feature upgrade in Intelligence TV)

Led the end-to-end development of a data-backed feature (Audience Mode) within the TVI platform, aimed at improving digital ad revenue through smarter media planning. By analyzing ACR and DSP data, uncovered key contextual and geographic insights that inform high-conversion strategies. The solution was validated through a successful POC, and is now being scaled to new regions.

• Developed a data-driven recommendation engine using ACR signals and DSP conversion data to identify high-performing combinations of geography, context, and frequency.
• Conducted proof of concept (POC) and finalized logic, data sources, and feed design for robust feature delivery.
• Defined overlap thresholds to filter noise and generate accurate, actionable insights for media planning.
• Authored comprehensive unit test cases to ensure data accuracy and system reliability pre-launch.
• Facilitated geographic rollout of the feature to new regions including Australia (AU) and Canada (CA) after successful initial deployment.

Metrics Enhancement and Insight Generation

• Implemented Incremental Reach Metrics for Post-Campaign Analysis Dashboard
• Implemented Conversion Rate Metrics for Post-Campaign Analysis

Ad hoc Project Contributions

• Developed Automated PPT Solution for Streamlining Client Presentations by fetching data from various API's
• Developing String Matching Solution for Advertiser Mapping for creating new insights

• Road Express Network Design
• Worked on network design to improve service and reduce cost by consolidating loads at hub.
• Built various tools in python and generated reports to identify cost savings opportunities.
• Decreased LH fleet cost by 2% and improved service efficiency by 5%.
• Created operation level plans to handle High Occasional load without choking Service center or small hubs
• Service Center Optimization by location and Number
• Using K-mean algorithm and elbow method, identified optimal number of service center for the city
• Calculated weighted centroids for clustered pin codes to enhance location targeting
• Network Design By Reinforcement Learning
• Automated the Line Haul network using DDPG algorithm
• Assisted in framing the business logic to create the environment.
• Direct Delivery
• Used Knapsack and VRP algorithm to reduce the last-mile delivery cost.
• Dashboard
• Created dashboards using Dash library for management overview.