iion.io specializes in in-game advertising through its comprehensive platform, immersiion. This platform offers a range of ad types, including in-game display, video, and audio ads, allowing brands to integrate their messages seamlessly into gaming environments without disrupting gameplay. The platform supports a variety of formats such as static ads, sponsored game content, and advergames, all designed to blend naturally into the gaming experience​.Key features of iion's approach include:In-Game Ads: Non-intrusive ads placed directly within the game environment, such as virtual billboards or branded items, which enhance the gaming experience while promoting the brand.Around the Game Ads: Ads displayed during breaks or loading screens, like banners and rewarded videos, which engage users without interfering with gameplay.Away from the Game Ads: Ads targeting gamers outside of the actual game, on platforms where they consume gaming-related content​

As the Head of Data Science at ReBid, an Advertiser's CDP, I lead a team in developing cutting-edge AI solutions that revolutionize campaign management and optimization. My focus is on conceptualizing and driving the development of innovative AI tools that empower advertisers to make data-driven decisions and achieve unprecedented performance.Key Achievements:1. AI CoPilot: Developed a comprehensive AI CoPilot for media planners and campaign managers, combining AI Assistant and Dashboard to optimize campaign performance and drive data-driven decision-making. a. AI Assistant: Developed an innovative AI tool using the Langchain Framework and GPT 4, employing a multiple AI agentic architecture to provide marketers with deep insights into ad and campaign performances through a conversational interface, offering optimization suggestions and advanced reporting functionalities. b. AI Insights Dashboard: Implemented a real-time, AI-powered insights dashboard enabling users to analyze crucial metrics (ROAS, Transactions, Expenditure, CTR, CPA) and gain valuable insights on correlations between these metrics and various ad metrics, empowering advertisers to identify inefficiencies and optimization opportunities.2. AI Media Planner: Created an innovative tool that automates budget planning across Google Ads, Facebook, and Amazon Ads using curve fitting on historical returns and simulations to optimize budget allocation and maximize performance.3. Customer LTV and Churn Modeling: Developed sophisticated ML solutions using Beta-NBD and Gamma-Gamma fitters to predict high-value, low-churn audiences, resulting in 7.5X ROAS for a clothing and lifestyle client on Facebook MOF targeting.4. User-Item Collaborative Recommender System: Spearheaded the development of a state-of-the-art system to trigger personalized product recommendations through targeted email and SMS campaigns for a fashion and lifestyle brand, employing advanced data science techniques.

Motive builds technology (AI powered applications that automate vehicle & equipment tracking, driver safety, ELD compliance & more ) to improve safety, productivity and profitability for the businesses that power the physical economy.Utilized advanced time-series forecasting techniques, specifically Univariate SARIMA (Seasonal Autoregressive Integrated Moving Average), to project the Marketing Revenue to Lifetime Value (LTV) ratio across distinct account segments. This robust model, with an average Mean Absolute Error (MAE) deviation of less than 5%, enabled precise benchmarking and monitoring. It provided actionable insights for fine-tuning marketing strategies across a wide range of account segments, thus enhancing marketing precision and efficiency.Undertook the design and interpretation of A/B tests for website optimization using rigorous statistical analysis methodologies, ensuring statistically robust results by careful evaluation of statistical power and significance. This sophisticated, analytics-driven approach significantly enhanced organic conversion rates on Motive's website, leading to higher user engagement and improved business outcomes.Led the transformation and refinement of existing marketing data sources and Key Performance Indicators (KPIs) across an integrated digital marketing suite, including Paid Search, Social Media, and Programmatic Display channels. This was part of a pioneering initiative with a dedicated Marketing Analytics team. The overhaul improved data quality and visibility, driving data-driven decisions that optimized marketing performance across channels.

MiQ is an independent Marketing Intelligence company operating in the Ad tech industry. My current role at MiQ challenges and enables me to utilize my problem decomposition and professional research skills to solve a multitude of client problems across the entire planning, execution, tracking & measurement cycle of their marketing system, while also striving to ensure an independent positioning of MiQ’s Data Science brand in the industry. Audience Prospecting Algorithm Development: Leveraged data science principles to design, develop, and deploy a cost-effective audience prospecting algorithm. This model was aimed at attracting highly engaged first-time users to the client's website, resulting in over 2.5 minutes of site activity per user per $1 spent—4-7 times higher than the industry average. I am presently engaged in scaling this solution to a comprehensive product offering.User Engagement Propensity Model: Co-created an innovative on-site media measurement Key Performance Indicator (KPI) using a data-driven user engagement propensity model. This tool provides clients with advanced metrics beyond the standard site-visitation/ROAS/CPA, focusing instead on the quality of traffic driven by campaign partners. This innovative approach secured a $4.9Mn global commercial partnership with a leading American MNC technology company, among other commitments.Ticket Sales and Attendance Forecasting: Employing statistical modeling, I designed a predictive tool for forecasting daily ticket sales and imminent match attendance for an American Major League Baseball team. This model provides 90-97% YoY accuracy over different phases, serving as a vital aid for campaign planners.

A global Marketing Effectiveness consultancy with Analytics & Measurement at it's core.Being a part of the Marketing & Media analytics wing of Gain Theory, these are some of the analytical pieces that I have worked upon:-Churn Reduction through Advanced Analytics: Improved the customer attrition metric for a leading consumer engagement brand by defining and identifying patterns of churn. Using Recursive Feature Elimination (RFE) scoring for user behavior mining, I developed strategies that yielded actionable insights to mitigate churn. During the trial run, these measures enhanced customer retention to 77%.Early Adopter Identification through Statistical Modeling: For a premium lifestyle brand, I designed a statistical model to identify potential early adopters of newly launched services. This model prospectively identified users who were not only likely to try out new services but also likely to act as organic marketers for the client.Media Channel Viewership Analysis and Audience Segmentation: Performed an in-depth analysis of content viewership drivers and carried out audience segmentation for a leading Hindi GEC media channel based on demographics, timing, and content preferences. This work served as an independent component of a central planning and monitoring dashboard for the client.Market Basket Analysis for Upsell and Cross-sell Opportunities: Utilized Association Mining techniques to identify upsell and cross-sell opportunities. The association rules were used in conjunction with RFM (Recency, Frequency, Monetary) clusters and product's LSM (Living Standards Measure) value to target customers for associated products.

As a key player in performance metrics management, I took on the responsibility of extracting, collating, analyzing, and presenting pivotal performance indicators across a multitude of projects to diverse stakeholders. This role required a deep understanding of data management, analytics, and communication, as I worked to provide clear and concise presentations of complex data.I further utilized my expertise in business intelligence (BI) to create process templates for data exploration. This initiative not only streamlined our data analysis process but also enhanced the effectiveness of our BI team by providing a structured approach to data exploration.Beyond these, I also played an active role in risk management and process optimization within the organization. I regularly conducted Root Cause Analysis (RCA) to identify the underlying reasons for performance discrepancies or issues. This critical analysis fed into risk prioritization exercises, where I helped to identify and rank potential risks based on their potential impact on our operations.Further, I facilitated the development of mitigation strategies for high-priority risks, ensuring that our team was prepared to handle any eventualities effectively. Moreover, I took the lead on process optimization initiatives, continually seeking opportunities to improve our methods and boost efficiency.Through all these roles, I aimed to create an environment of continuous improvement, grounded in data-driven insights and proactive risk management.

I spearheaded a meticulous evaluation of our existing value stream, mapping and scrutinizing each step of the production process to identify and eliminate non-value-adding activities. This exercise was vital in improving our operational efficiency and productivity.A significant part of this initiative involved revising our inventory management techniques. By streamlining this process, we were able to reduce bottlenecks and improve flow. Additionally, I implemented changes to our sampling inspection methods to increase accuracy and decrease wasted time and resources.These strategic modifications led to substantial improvements in our Net Value Addition Time, increasing it from a meager 4.4% to an impressive 19.87%. This tangible result not only demonstrated the efficacy of our process enhancements but also contributed significantly to our overall operational efficiency.