Alex Veen Email & Phone Number

San Mateo, Ca, Us

I lead the ML/Data Science team covering ads, AI tenant apps, identification, and intent.

Staff Data Scientist at the Ads organization. Developed a price prediction model used in real-time bidding (RTB) to optimize the auction bid price for online ads.Worked on models used in real-time bidding to predict outcomes after ad exposures such as clicks, site visits, viewability, and user engagement.

Planned Supply Levers (Driver Incentives)Led a team of data scientists owning various driver incentives programs, such as driver engagement and driver resurrection. The team builds and maintains HTE models to target drivers with efficient incentives so they drive when and where they are needed the most. The team is also in charge of measuring and reporting the efficiency of the various incentive programs based on always-on experimentation in order to determine optimal spend levels for market management, trading off efficiency vs growth. Moreover, the team builds new incentives products and runs A/B tests and analyses to make ship decisions.

San Francisco, Ca

Acquisition Incentives and Referrals, Marketing Automation PlatformDesigned driver acquisition and referral incentives and drove the team’s experimental strategy. Worked on models to automate and scale the company’s user acquisition and retention efforts. This included workflows to set ride requirements, bonus and guarantee amounts, predicting user activation, productivity, and LTV. Designed a method to detect and monitor incentive abuse (fraud).

Menlo Park, Ca

Core App Monetization (Feed Ads)Supported video ads product development and strategy. Supported launch and roll-out decisions based on A/B testing, quantitative analysis, and statistical modeling.Opportunity sizing, goal setting, and impact measurement for new products and features. Tracking and forecasting of KPIs and other metrics.

Mountain View, Ca

Quantitative Marketing (Advanced Measurement Technologies)Developed tools to measure and quantify the effectiveness of ads based on an advanced experimentation system (A/B testing).Developed tools to measure and quantify brand metrics such as consumers' engagement with a brand and a breakdown into Paid, Owned, and Earned media exposure.

New York, Ny

Analytics SolutionsLead analytics projects at the Research and Analysis group at New York Life Insurance.Lead the technical aspects of a large fraud investigation. Developed a fraud scoring algorithm based on sales patterns, lapse rates, contract changes, analysis of links, and the time distributions of relevant events. Developed a dashboard for monitoring of potential fraud and other business quality issues.Worked with New York Life’s corporate venture group to evaluate the technical aspects of high-tech startup companies – in particular the plausibility of claims in the Analytics / Big Data field. Designed and managed a Proof of Concept for a startup company to test and evaluate their algorithms and approach.Performed detailed study on LTC insurance claims based on a logistic regression as well as alternative approaches related to survival analysis. Analyzed client-related variables as well as agent sales patterns and experience.Worked with actuaries on the development of a new mortality table with risk adjustment factors. Worked out implementation issues of existing approach to more modern methods such as Logistic/Poisson regression, survival analysis, Accelerated Failure Time models, etc.Designed the technical approach and performed a simulation study to assess the company's exposure to reinsurance companies.Worked with Market Strategy to explore the use of text analytics for generating “digital sales leads”.Developed an approach to evaluate underwriting risk scores and showed how they can be used to automate some parts of the life insurance underwriting process.

Yorktown Heights, Ny

Research Staff Member in the Statistical Analysis and Forecasting group of the Business Analytics and Mathematical Sciences Department of IBM ResearchResearch in time-to-event forecasting, point process modeling, model evaluation, mortgage analytics, patent analytics, call center analytics, statistical seismologyPublished several academic articles and filed several patent applicationsDeveloped statistical and data analytic models such as ...A CRM “best time to call” model used in day-to-day call center operations based on customer-specific contact historyDeveloped a method to forecast financial metrics and key performance indicators (KPI) to facilitate operational target setting in an outcome-driven business modelDeveloped a sales forecasting methodology for products at different stages in their product life cycleDeveloped a method for comprehensive contact channel explorationDeveloped statistical models for mortgage servicing using forecasting and time series techniquesDeveloped a statistical model that forecasts when customers pay their billsServed as the technical project lead of a team of six developers (database architect, ETL, Java, Cognos, and JRules developers) to build a Credit Performance System. This analytics platform is used for reporting and forecasting mortgage delinquency roll rates and associated performance metrics.

Diplom, Economics And Business Administration

Ph.D., Statistics