Helping the team grow our Small & Mid sized advertiser Business [SMB]. Built data science practice to collaborate within a cross functional setting including sales, marketing, qualitative research, product, engineering & analysts. • Address systemic bias within ad platform allowing SMB advertisers to fairly compete with Fortune500 advertisers including issues such as ads cold start, usability experience and audience targeting• Partnered with business marketing to construct advertiser growth engine using paid/organic search marketing, emails, in-app notifications, lead scoring, sales outreach• Combined advertiser segmentation & sales motions to create sales treatment plans that improved advertiser performance & were AB tested to prove incrementality• Coordinate web scraping of advertiser sites for lead scoring, segmentation, vertical classification, and methodologies to control advertiser quality for metrics reporting• Fast paced environment providing constant monitoring & guidance to various levels including executives during turbulent times for advertising industry

Transitioned to work on notifications within the Growth team to help solve slumping user activity. Architected event logging, testing framework, data pipeline, metrics definition & dashboards to monitor growth notifications, which quickly became a key growth lever for the company. Instrumented a hierarchical AB test framework to accurately measure pros & cons of all new growth notifications, called Responsible Notifications. These data foundations were then used to implement notification personalization using common machine learning methods. Overall the growth notification effort has been critical to maintaining user engagement during adverse consumer reactions. Due to the major success of the growth notifications effort, began comprehensively leading measurement efforts for all Snapchat notifications, including delivery funnel, engagement impact, downside measurement, campaign targeting and execution. Also became a measurement lead in many active consumer marketing channels driving a holistic approach to multichannel marketing at Snapchat, most notably Notifications, Email, Paid User Acquisition, Preload deals and SMS.• Pioneered user targeting techniques at Snapchat, using behavioral, demographic & friend network data signals, to optimize campaigns across many channels for reach & impact• Partnered closely with consumer marketing team to create product education campaigns for new Snapchat features• Popularized challenging downside metrics within the company; both trend level and incremental; application uninstalls, system notification disables, and application open bounce rate• Instrumented novel experimental techniques to measure long term effects of marketing campaigns including long term user versus rotating randomized user & message holdouts• Architected User Acquisition analytics platform from inception and guided to support large budgets spread across diverse channels & ad partners, while also providing important insights for ad campaigns

Made major contributions to company revenue measurement, growth strategy and intellectual property. Hired as the first data scientist on the Revenue Analytics team, worked closely with ad measurement partners to understand & communicate campaign results to advertisers. This included novel visitation lift studies which large retail advertisers used to measure ROI for our location targeted ad units. Contributed significantly to understanding of product changes & relationship to ad inventory. Successfully showed that more ad inventory was not necessarily the best choice for the user, and these insights ultimately reshaped the user experience. Researched novel method for clustering users based on weekly & daily usage patterns, which helped support user targeting efforts in advertising and notifications. Transitioned to work on notifications within the Growth team. Architected event logging, testing framework, data pipeline, metrics definition & dashboards to monitor growth notifications, which quickly became a key growth lever for the company. Instrumented a hierarchical AB test framework to accurately measure pros & cons of all new growth notifications, called Responsible Notifications. These data foundations were then used to implement notification personalization using common machine learning methods.• Worked closely with 3rd party measurement companies, Datalogix, on in-store purchasing lift• Defining Snapchat personas using behavioral segmentation, friending dynamics & application activity• Pioneered measurement of ad campaign visitation lift, led to acquisition of company Placed• Discovered significant improvement in custom audiences ad targeting using friend graph• Extensive experience using Google Cloud Platform at scale of 200+ million daily active users• Advanced implementations using BigQuery SQL, Looker dashboards, Airflow pipelines, XGBoost & Tensorflow for machine learning

Advising founders on analytics, machine learning, content strategy & media partnerships

Teaching data & analytics to product managers

Informed Instagram Ads on key product decisions with analysis & drove significant changes to Facebook Ads integration plans. Work was clustered in 3 of the major areas: porting ads from Facebook to Instagram (demand analysis), understanding ad load on Instagram (supply analysis) & Instagram commerce (Small-Medium sized Businesses). Each analysis had strategic insights for product, marketing, engineering & executive teams & shaped the current Instagram Ads ecosystem. Provided important insights on how Instagram business accounts use the 3rd party apps, indicating a large revenue opportunity in adding analytics, content management & marketing automation support for businesses on Instagram. These analyses helped shape team discussions around how to best execute an Instagram commerce plan to best serve the Small-Medium sized Business community on Instagram.• Built machine-learning models to classify Instagram accounts into advertising verticals• Developed many insights into how to optimizing the video experience on Instagram• Proved Instagram revenue opportunity for Website Clicks & Mobile App Installs to be greater than Page Post Engagement which proved a critical pivot in order to meet Instagram quarterly goals • Showed that a small number of power Instagram users saw majority of ads (power law distribution) & how quality levers can be used to better distribute the ad load (measured via gini coefficient)• Exposed large gaps in the supply chain, such as unmatched Instagram users to Facebook IDs• Extensive analysis into how we might shape the Instagram commerce business• Analyzed content production patterns for Facebook Pages with associated Instagram accounts & built a revenue model showing how much we might earn on Instagram using boosted posts• Spoke at Big Data & Telco Panel Discussion in CTIA Super Mobility 15’ on optimizing customer network experience

Initiated a company-wide data driven understanding of YouTube & online video. Insights were developed in every department from Execs & Finance to Ad Sales & Programming. Efforts in segmentation & optimization played a critical role in turning the business model from an art to a science. Was the main point of contact for all data related presentation of Maker to Disney, which played a critical role in telling the Maker story. The presentations ultimately led to acquisition for $1B.• Competitor analysis and valuation of content libraries using Freebase & Content ID claim history• Traffic modeling in various contexts using transcoding bitrates & network social media reach• Data warehousing using Amazon Redshift & Pentaho data integration for ETL• Business Intelligence via Tableau reporting server & D3.js for talent dashboards• SalesForce Talent CRM integrated to provide churn analysis & acquisition effectiveness KPIs• Content classification algorithm developed which segmented channels into business units & verticals• Played a decisive role in the Disney Acquisition

Collaborated across many departments to execute important business objectives in areas including customer acquisition & retention, product recommendation engine, inventory management & optimization, social & email marketing strategy and financial forecasting. Hired and managed a team of database engineers, business analysts & data scientists to instill data driven culture at one of leading social commerce companies. Surfaced many valuable business insights into customer purchasing habits across several verticals that directed company strategy towards unified shopping experience across stores. Transitioned analytics team from engineering to focus on database marketing. Advanced customer segmentation & behavioral targeting provided by analytics became the cornerstone marketing decisions & critical in daily campaign execution. • Worked closely with media buyers to identify ROI positive channels and optimize campaign targeting & creative and experimented with micro-targeting campaigns using Facebook Ads API & Exchange• Created predictive customer segmentations based on behavior & engagement measures used to evaluate success of marketing campaigns• Taught SQL & statistical modeling to co-workers inside & outside the analytics team• Worked cross-functionally to design & implement real-time product recommendation system from prototype to internal API• Statistical models to support product/marketing efforts including Email Response Rate, Customer LTV/Retention/Churn, Store Cross Promotion & Monthly Product Sales• Implemented Wharton School of Business LTV Model, Buy till You Die using R + Vertica• Supported product AB testing system design, reporting and encouraged company-wide testing • Maintained TB-scale Vertica data warehouse using open source Pentaho data integration tools, OLAP dimensional modeling using Mondrian, Tableau visualization & Hadoop/Mahout for ML

Fostered an analytics culture for a social gaming veteran; provided the quantitative basis for a largely qualitative business. Gave management new insights into their business operations by defining a wide range of core KPIs and introducing customer segmentation models. Led to the formation of a specialized marketing team focused on creating loyalty programs for engaged customer segments. Hired and trained a team of 5 direct reports and trained many additional company personnel. Instilled AB testing methodologies within several game teams helping to develop valid test environments & use statistical methods to determine success. Utilized modeling techniques that are novel within the industry to understand retention/monetization.• Perfected & taught Vertica SQL aggregation techniques• Implemented a Tableau to allow less technical personnel to quickly deep dive into data• Constructed LTV models which included analysis of up to 15 levels of viral network• Aided Marketing in understanding Yield-based methodologies• Extensive research into game distribution on Facebook and iOS• Drove company efforts for extensive game event tracking and user techno-graphic profiles• Introduced Hudson as a management system for Graphing & ETL processes• Promoted awareness of data quality issues, & designed data assurance systems• Aided in the maintenance of ETL processes & OLAP systems• Led reporting efforts surrounding game economy/feature optimization• Advanced analytics including Survival & Churn Analysis for retention, Logistic Regression to identify segment predictors, Decision Trees for game optimization, User Clustering using game behavior & PCA to identify user groups based on Facebook Likes

Pioneered analytics and reporting infrastructure for major game titles including Nightclub City, MyTown, InCrowd and Deejay. Defined data storage requirements for in-game event tracking, and used the data to provide valuable business intelligence to all areas of the business. Kept up with fast-paced demands from all areas of the company often requiring information on our 20 million plus user base. Worked with several industry leaders regarding innovative technology and ideas ranging from Protocol Buffers, Redis, Ad Exchanges, Viral Game Mechanics, Virtual Item Branding, In-Game Recording Artist Promotion, Location Based Advertising and many more.• Setup data aggregation processes using Cloudera Hadoop & Column-Based Storage Engines• Maintained data aggregation storage & reporting processes after deployment• Provided instrumental facts to monetization & user acquisition personnel including lifetime value of various user segments, an understanding of Facebook traffic sources, long term effects of cross-promotion activities, segmentation of user base based on viral value• Guided game designers to use AB testing methodologies and to steer away from the one-size-fits game experience and move towards personalized game experiences• Performed complex data-mining on in-game event data to find actionable information for game designers to understand how to structure game content in new releases• Conducted detailed testing and analysis on user interface efficacy to find bottlenecks and exit points in game engagement funnels • Directed company towards a universal virtual goods store engine to be used across different titles. • A single virtual goods store engine could utilize centralized content management and price optimization systems.

Acted as the analytical manager for the monetization platform, reporting directly to company executives and major publishers. Created transparency for business performance by developing and managing reporting infrastructure built from open source software packages. Had a critical role in maintaining revenue streams by implementing several machine learning processes that optimized and cleansed advertising inventory. Was an important advisor to the technology team in helping identify revenue bearing improvements to the platform. Worked closely with business development team to identify trends relevant to business strategy and compiled advertising statistics to be used in marketing collateral. Pioneered business intelligence processes to monitor revenue/traffic trends using segmentations such as user demographic data, advertising units, publisher networks, gaming platforms and temporal segments. Successfully trained and managed personnel of varying qualifications to take ownership of projects I created that had grown to be critical for the business.• Findings influenced company to aggressively pursue direct marketing strategies• Constructed advertising AB testing framework and tested several R&D hypothesis like ad priming and other psychologically active designs• Wrote competitive traffic/revenue analysis for publishers that was instrumental in acquiring more advertising space for the company• Researched and helped write detailed industry white papers on advertising supported by virtual currencies for publisher education• Assisted R&D on several cutting edge projects such as computer generated game content, game recommendation engines, virtual currency escrow accounts, personalized advertising frameworks, virtual goods marketplace pricing model, user & advertising classification/clustering approaches

Responsible for financial modeling, database administration, reporting and code refactoring used by the corporate credit trading team during the peak of the credit crunch. Spoke frequently with key credit traders and R&D finance professors to create project management goals and timelines. Assisted the credit team respond to credit market dynamics with ad-hoc reporting and database features for better market data transparency. In several cases, proved credit traders' market intuition using linear regression and hypothesis testing. Researched and implemented several proprietary financial models and created model statistics used in company marketing collateral.• Market correlation model using Gaussian Copula for credit default index trading • Heavy C# coding using Monte Carlo simulations and Stochastic Calculus theory• Extensive use of Microsoft SQL server reporting services• Maintenance of financial data services pull technologies• Re-factored proprietary corporate bond valuation model

Developed an image analysis tool for the analytical arm of the research team used to analyze neural network signal propagation movies created by the wet lab arm of the research team. Kept close communication with graduate students to ensure the tool was useful in exposing the network topology.• Built a JAVA plugin to visualize network dynamics in ImageJ