Dhanush Kishore

- Developing and optimizing Skyscanner’s core flight ranking model, which determines the order of flight search results shown to users - Building and testing deep learning models offline, and validating improvements through large-scale online A/B experiments to boost relevance and user conversion - Built Skyscanner’s in-house Bayesian A/B testing library, now the foundation of the company’s experimentation platform

- Designed complex AB experiments and developed experimentation strategy to drive business-relevant product metrics - Researched statistical measurement methodologies to quantify incrementality from marketing activities - Developed various predictive models in the product and marketing domains - Developed methodologies to use Monte Carlo simulations to quantify risk and uncertainty in product decision making

- Built a predictive ML model to identify product sign up funnel flow fallouts with a high probability of being high spending users, in order to target them with marketing actions Developed churn prediction ML model enabling product team efficiently allocate sales representatives to high value-at-risk users Developed an NLP and ML-based sentiment analysis web app to enable business teams to automatically obtain actionable insights from product user reviews

- Engineered a complex SQL pipeline to fuzzy match disparate hospital records of various pharmaceutical companies with those of a pharmaceutical distributor , improving the efficiency of invoicing and saving 10 manual labor hours each week Other Achievements: - Ranked 1st in Fractal Machine Learning Hackathon (April 2019) - Ranked 1st in Fractal AI Triathlon Stage 1 (Jan 2019) - Ranked 3rd in Fractal AI Triathlon overall (Jan 2019)

-Developed an ML and NLP based web app to automatically identify tweets about instore disturbances, and make the best guess about the store it refers to, enabling the Compliance team to respond to such incidents faster - Developed KPIs for Compliance at global and regional levels, and dashboards to track them, surfacing insights to leadership

@World's largest retailer: - Forecasted daily cash requirements for instore check cashing service in tax refund season, driving 30% reduction in instances of cash running out - Built a kiosk recommendation solution to optimize kiosk space utilization at retail stores, driving $5M in annual income - Developed a dashboard to enable business stakeholders to obtain an overall snapshot of the revenue growth of the consumer and financial services business