DANIEL FOLEY

I'm a Principal Data Scientist focused on automating and modernizing drug pricing for the companies largest line of business.

• Led the migration and automation of 4 pricing models in companies largest line of business, significantly improving the scale and efficiency of generic pricing updates.
• Designed and deployed a new modelling tool, facilitating scenario analysis and providing key insights to shape the following year's strategic pricing direction.
• Lead a group of Data Scientist focusing on identifying and executing automation projects across network pricing.

• Part of team of Data Scientists and ML engineers responsible for producing over 1 million daily LTV predictions for consumption by user acquisition operations.
• Designed a new Bayesian methodology to produce LTV predictions to guide the business in determining marketing spend for new game launches.
• Developed a new UA experiment dashboard to help assess the risk return tradeoff and make faster decisions regarding new UA campaigns which account for approximately 15% of total marketing budget.
• Conducted many root cause live ops analyses as the primary data scientist for two of our live games, involving clear communication of complex topics to a non-technical audience.

• Developed and maintained core player lifecycle models used to predict user churn, repeat payment and first time conversion propensity for each of the companies 4 apps.
• Worked closely with product teams to integrate core models and design AB tests resulting in conversion rate uplift of 2%.
• Built and maintained ETL pipelines for different projects including player lifecycle and in house segmentation system.
• Designed a new methodology and provided comprehensive analysis and recommendations underpinning the new loyalty program in the company.

• Led strategy and implementation of reproducible analytical pipelines (RAP) to automate production of statistical reporting in DWP.
• Developed data pipeline for user logs and created dashboard to track user engagement metrics helping to improve insight into how users interact with the departments products.