As the Director of Product Analytics and Experimentation at PlayStation, I oversee a team responsible for delivering insights that inform product strategy, roadmap planning, and decision-making across the organization. My job responsibilities include:- Lead the development and implementation of data-driven solutions that enable PlayStation to identify new growth opportunities, optimize product features, and enhance user experiences through experimentation- Collaborate closely with cross-functional teams, including product management, engineering, and design, to identify key business objectives and define experimentation strategies that drive product improvements- Lead the development and execution of experiments to validate hypotheses and inform product decisions. Design, execute, and analyze experiments, leveraging A/B testing and other techniques to measure the impact of product changes and drive continuous improvement- Ensure the accuracy, completeness, and timeliness of our product analytics data and experimentation results. Regularly communicate key findings and insights to senior leadership to inform key business decisions and influence strategic planning

- Thought partner and single point of contact for 50+ Product Managers for all PlayStation products: Gaming, Social/Communications, Web & Mobile, Media (TV/Video, Music), Retail/Store Monetization, Console User Experience, Commerce, Accounts & Identity- Led PS5 launch analytics for entire product organization at PlayStation involving Product Managers, Engineering and UX Research teams delivering 70+ key projects during PS5 global launch- Responsibilities include helping product managers define KPIs for the various product features and measure their success. Design and conduct rigorous analyses and experiments to drive improvements to key product features and influence the product roadmap- Leading a team of product analysts, data scientists and data engineers - Responsible for hiring & career development- Segmentation, BI reports, A/B testing, Cohort analysis, Causation analysis, Forecasting, Churn projections, Store analytics, Funnel Conversion rate, Revenue projections, Post launch impact, User engagement studies

Responsible for managing product analytics and data science, global client development, consulting support, project delivery, people management, recruitment and firm building for the Healthcare practice at Fractal.Optimization, Pricing and BI solutions for a Fortune 10 Healthcare company (leading a team of 10)• Led a team of data engineers and data scientists to develop a tier 1 application that helped optimize the vendor contract management process driving $20M savings in EBIT• Developed a data harmonization platform to provide unified customer view • Developed a manufacturer facing scorecard for 1000+ manufacturers that supplied to the client, evaluating them across multiple supply chain categories • Designed a Pricing guidance solution for new customers that had no purchasing history with the clientProduct analytics for a design software company (led a team of 4) - San Francisco, CA• Developed usage-based segmentation framework to assess each customer’s attachment to client’s product by assessing the customer usage pattern, after 3 months of purchase (onboarding), between the 4th and 9th month after purchase (adoption) and 3 months before renewal (retention)• Recommended a customized marketing/contact strategy as per the segmentation to create a personalized nurture strategy for each customer and increase company’s customer base that increased customer NPS by 10 points and retention rate by 5% over a 6 months period

Data Science Models for customer lifecycle management for a direct Personal Auto US Insurance company (led a team of 5) – San Francisco, CA• Developed a forecasting solution to predict the monthly Average call handling time at the company’s customer contact centers for the next 6 months, to enable adequate staffing• Developed a loss ratio prediction model to forecast the first-term loss ratio of new policyholders in its auto insurance line of business, to enable accurate policy pricing• Built a channel of conversion model that predicted the preferred channel of conversion for all auto insurance quotes initiated on the client's online portal, for appropriate reach out strategies• Built a model to predict the dollar-benefit of pursuing customers for an increase in policy premiums, customers who were believed to have provided incorrect information at the time of policy purchase

Lead AI Consultant - Revenue management for a leading US healthcare provider (led a team of 5) • Developed payment prediction models to increase the hospitals’ revenue (across multiple systems and states in the US) by improving the collectability of the patient’s portion of medical expenseCustomer Analytics solutions for a leading European retail bank (Data Scientist) • Developed customer churn prediction models to predict customer attrition and introduce relevant retention strategy on the basis of customer and product segmentation • Developed cross-sell/up-sell models to find the right next best product for the client’s customer baseMarket attribution modeling for leading direct insurance company in Japan (Data Scientist, Jun 2014 – Sept 2014) • Developed an attribution model to attribute credit for driving sales and other KPIs to marketing channels, esp. broad and digital media

Discretionary Pricing Model for a leading Commercial Insurance company in the US (Data Scientist) • Built risk prediction and pricing models for the insurance company to identify high-risk customers and price them appropriately to lower the combined ratio• The models developed and deployed helped bring down the combined ratio for the commercial line of business by 5%

Handle the discretionary pricing models for Farmers Insurance US. Building the models and keeping a track of model performance in different states of US.