We are team that focuses on direct to consumer applications of ML. We use a combination of pre-trained services and customized models to build products in recommendations and search, video services and model management.

ML frameworks that power CBSi products

Tracking, QA, Ingest, Data Infrastructure and Architecture, Data Science Microservices

Combined two data-centric teams for broader coverage and support. The team is responsible for the following:* Tracking and Implementation fo internal and 3rd party systems across CBSi* QA/Testing of implementations as well as maintenance* Data Engineering of pipelines/micro-services where necessary* Data Science solutions for sites

Leading new Data Products group under Research & Data Products. Responsible for CBSi projects involving data and text mining/machine learning/predictive analytics. The team also built out custom tools for internal clients on a Mongo/Django/Python stack that makes extensive use of D3.js.I've built up a team of Informatics Engineers, Applied Mathematicians and Software and Mechanical Engineers from scratch to deliver tools and solutions that drive new views into the business across all CBSi properties. We developed tools for Social, Revenue, Web Analytics, Quality Control, Ad Inventory and Partner Video.

As part of a Central Market Research Group conducted many data mining/analytics projects across CBSi. The responsibilities included:* Text Analytics on social media and user-generated commentary* Investigating Brand association with various CBS properties using text mining techniques* Collaborated on building out a Social TV tool in 2010 using internal and external sources* Project to surface restaurant reviews surfaced from Chowhound boards* Modeling the Games Market based on Games sites data

• Statistical models and analysis of enrollment with budgetary impact and other data for the campus, data mining, modeling and predictive analytics for budgeting and admissions.• Developed Markov Chain models to predict enrollments 9 months in advance to assist in revenue flow forecasting. Model accuracy achieves less than .01 error.• Was responsible for evaluating data mining tools and systems. Worked with management to negotiate the implementation of SAS office-wide.• Set up and established the SAS data mining shop for my unit. I worked as a systems administrator and modeler. • Created decision trees, logistic regressions, neural network models for predicting student drop-outs in special populations. These models were crucial for revenue flow and risk analyses for the university.• Initiated building space utilization models using PCA and association models. Models are crucial for distributing class times and saving money on building upkeep.• Wrote template data mining processes to reuse in other analyses.• Lead initial analyses and modeling of student flow from matriculation to graduation. Models use Segmentation analysis, Markov Chains, logistic regression and decision trees to predict student plan and course selection.• Wrote special report on graduate student registration patterns. Using trend analysis and time series, model predicted enrollment levels at various points in time. Project report impacted revenue forecasting models for the university.• Conducted backtesting of all predictive models every 6 months.

• Lead workshops on Unix, Perl, CSS, XHTML, Dreamweaver, Flash, Photoshop, and Illustrator.• Developed new workshops on Perl scripting, and Unix shell scripting.• Edited and updated workshops on CSS and XHTML.

In my functional position, worked in consultant R&D of new tools. Introduced the mind mapping technique for client interviews. Other highlights:• Worked closely with several large Consumer Retailers on marketing analytics & forecasting for increasing ROI on existing locations. Price and Trend Forecasting Analyses with impact on budget lead to large increase in marketshare. • A strategy consultant for many Fortune 500 companies in consumer electronics, pharmaceuticals, banking, and retail. Consulted for Best Buy, Lucent Technologies, Wyeth, AstraZeneca, PNC Bank, and Diageo.