I provide technical and strategic guidance to early startups on topics around Data, Machine Learning, and AI.

Responsible for a team of 50 Data Engineers, Machine Learning Engineers, Analytic Engineers, Data Scientists, and Tracking specialists.• Led the transformation of the Data team to meet the Data Analytics Business requirements.• Put forward a new Data Team Blueprint.• Promoted a Data Steering Committee to align Company-wide priorities for Data.

Built and lead from scratch a team of 10+ ML engineers and specialists, and 10+ Data Engineers, SREs, and Tracking specialists• Led the creation of a first-rate data stack based on Kubernetes, S3, Kafka, Airflow, Spark, and Redshift.• Established the ML/AI function from scratch, defining sustainable ways of working with Product.• Contributed a compelling and sustainable company-wide AI/Machine Learning strategy.• Successfully shipped a number of impactful Machine Learning solutions. Prominent examples: - Fraud prevention: automated ML censoring of malicious forms. ~100 forms censored daily.
 - Automated lead scoring: optimized Google Ads Value Based bidding. +24% sales at -30% CAC
. - Real time display of time it takes to complete a form. +2% Form Completion Rate. 
 - NLP-based browser Auto-complete from raw questions text. +3% Question Answer Rate and -4.5% Time to Answer.

Established a team of Research and Data Engineers from scratch. The team's purpose was to bridge the gap between Research, AI Research and Engineering by productizing Machine Learning and AI models and providing intelligent user-facing services.• Built a led a team of 5 Machine Learning and Data Engineers, and SREs.• Developed the Data Infrastructure to run real time ML models, including a Data Lake, a job orchestration system, and a set of ML microservices.• Shipped an ML predictive model of Sleep Activity based on mobile sensors and a Mental Health Activities Recommender System.

As the most senior Data Scientist of the Insights team, I led essential initiatives in the context of online marketplaces :• Behavioral classification of customers into Personas segments.• Network analysis of buyer-seller interactions through messaging.• Automatic classification of user intent (to meet, exchange, buy, bargain) based on conversation content.• Creation of a real-time Bayesian evaluation of online experiments for the incipient internal experimentation platform.In addition, as an Insights Data Science ambassador, I also:• onboarded 20+ Data Analysts and BI Engineers into Jupyter + Spark + S3, • supervised Data Science Interns, • ran workshops on Deep Learning for Engineers,• ran workshops on Bayesian Evaluation of Online Experiments for Data Scientists, • and established the Fun Fact Fridays team activity of hunting for fun but insightful data facts.

Data analysis and modeling of complex dynamic biological processes.

Data analysis and Modeling of Pluripotency in Embryonic Stem Cells.

Development of Efficient Stochastic Simulation methods for Complex Biological Networks.

Development of Stochastic Simulation methods for Complex Networks.

Development of analysis tools for High througput Microarray and Sequencing data.Gene-expression analysis. ChIP-on-chip data analysis. Gene Ontology.

Customer Strategy & Sales Intelligence consulting in the Travel and Leisure Industry. Customer Segmentation, Datamining and MarketResearch strategies.

Probabilistic Data Tracking, Sequential Optimization Procedures and Linear and Nonlinear data dimensionality reduction (PCA, GPLVM, Neural Networks). Image Sequence Analysis. Assistant teacher of Bioinformatics for Computer Scientists.