Image of Juan Huerta

Juan Huerta

Head of Data Science @ Dow Jones

Advanced Analytics, Data Science and Decision Science Leader in Finance

Greater New York City Area

Ranked #446 out of 8,920 for Head of Data Science in New York

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Juan Huerta's Email Addresses & Phone Numbers

Juan Huerta's Work Experience

Dow Jones

Head of Data Science

July 2014 to Present


Senior Data Scientist

May 2013 to July 2014


Vice President Advanced Analytics, Global Decision Management

April 2012 to May 2013

Juan Huerta's Education

Carnegie Mellon University


1995 to 2000

Boston University


Tecnológico de Monterrey


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About Juan Huerta's Current Company

Dow Jones

My role at Dow Jones is to help shape and drive Dow Jones' data driven vision, leverage Dow Jones vast data and information resources to identify product opportunities, build data products and maximize the value attained from such data. I lead a bright team of Ph.D. scientists with expertise in Machine Learning, NLP, Computer Science, Applied Math,...

Frequently Asked Questions about Juan Huerta

What company does Juan Huerta work for?

Juan Huerta works for Dow Jones

What is Juan Huerta's role at Dow Jones?

Juan Huerta is Head of Data Science

What is Juan Huerta's personal email address?

Juan Huerta's personal email address is ju****[email protected]

What is Juan Huerta's business email address?

Juan Huerta's business email address is h****[email protected]

What is Juan Huerta's Phone Number?

Juan Huerta's phone (212) ***-*271

What industry does Juan Huerta work in?

Juan Huerta works in the Online Media industry.

About Juan Huerta

📖 Summary

About Dow Jones: Dow Jones is among the most dynamic, creative and savvy news and information companies in the world. As a global leader in news and business intelligence, we''re newswires, websites, newspapers, apps, newsletters, databases, magazines, radio and television--including some of the widest-read and most-respected brands, like The Wall Street Journal, Barron''s, MarketWatch and DJX, our flagship news and analytics platform. Our media inform the discussions and decisions that are vital to the world''s commerce, while our databases make the business world more transparent. We continually develop technology to transform information into insight and prosperity. From over 50 countries and in over a dozen languages, we enlighten and inspire audiences with authoritative, differentiated and trusted content. About me: I am a specialist in the areas of: Machine Learning, Pattern Analysis, Statistical Modeling, Predictive Analytics, Big Data Analytics, Hadoop- Map Reduce, Big Query, Stochastic Processes, Sparse Data Modeling, Sequence and Time Series Modeling and Mining including HMM modeling, Computer Science, Graph Theoretical Algorithms (including social network analytics), Matlab, C, C++, Java, Scala, Python, Perl, Octave, R, Spark, Pig. Google Scholar Profile: of Data Science @ My role at Dow Jones is to help shape and drive Dow Jones' data driven vision, leverage Dow Jones vast data and information resources to identify product opportunities, build data products and maximize the value attained from such data. I lead a bright team of Ph.D. scientists with expertise in Machine Learning, NLP, Computer Science, Applied Math, Statistics, and Computational Biology. The focus of my work includes: - Research and development of large-scale NLP content processing pipelines, including methods for summarization, entity extraction and conflation, entity relationship discovery, topic modeling; Integration of graph based approaches with traditional Machine Learning methods, parallelization using Hadoop Map Reduce and Spark. Graph approaches. No-SQL databases, triple store databases, etc. - Modeling customers for Marketing, Acquisition and Retention: including hybrid market-driven & machine learning approaches. Development of predictive models for customer churn, audience modeling and segmentation, signal extraction for loyalty, engagement and affinity models, as well modeling of behavioral patterns. Integration of predictive, classification, and sequential modeling (Conditional Random Fields, Hidden Markov Models, Maximum Entropy Models) into our approach. Targeting and modeling using first party data. First and third party data joins. - A/B testing design of different aspects of our product. Customer lifetime value modeling as well as predictive modeling. Time series modeling, especially to identify characteristics of Newswires in effecting market movement. -Visualization prototypes, low latency low-footprint light NLP chunkers, fast scalable string and sequence matching, audience generation based on first party data, etc. From July 2014 to Present (1 year 6 months) Senior Data Scientist @ At PlaceIQ I focused on processing very large amounts of structured and unstructured, unrelated, location based data and – through a series of algorithms and processes of data cleansing, normalization, analysis, and machine learning – extract patterns, trends, intelligence and context from the data. This is a quintessential Big Data problem where Computer Science algorithms, Data Structures approaches, Graph Theory, Information Theory, Machine Learning, numerical and Signal Processing methods coalesce to create value from the raw data. Tools of the Trade: Elastic MapReduce, Java and Python streams. Scala. Spark. Pig. From May 2013 to July 2014 (1 year 3 months) Vice President Advanced Analytics, Global Decision Management @ At Citibank I focused on applying contemporary and machine learning techniques into "classic" business problems including customer modeling and segmentation, next best offer, contextual marketing, internal fraud detection, digital analytics including attrition, acquisition and common path traversal modeling. I also applied time series forecasting problems including balance prediction, and leading indicator prediction. Other work included root cause analysis for NPS survey analysis including structured predictive modeling and unstructured text analytics. Finally, I have also carried out work workforce predictive modeling including attrition, performance and promotion models. Machine Learning. Pattern Analysis. Statistical Modeling. Predictive Analytics. Big Data Analytics. Hadoop- Map Reduce. Stochastic Processes. Sparse Data Modeling. Sequence Mining, Computer Science. Algorithms. From April 2012 to May 2013 (1 year 2 months) Research Staff Member @ My work at IBM focused on developing novel machine learning and stochastic modeling algorithms to areas of natural language processing, machine translation, search and automatic speech recognition. My focus included sub sequence modeling and mining for large TM search, graph theoretical approaches to SMT, machine learning approaches to call center analytics including conversational and topic modeling, dialog management, call routing, robust speech recognition, etc. From 2000 to April 2012 (12 years) Research Associate @ Graduate Student on the Electrical and Computer Engineering Department, focusing on Robust Automatic Speech Recognition. From 1995 to 2000 (5 years) Research Staff @ Helped bring to life Dragon Dictate in Spanish. Massive data collection, Model development, Model discrimination algorithms, Developed Phono-morphological recognition improvements, HMM Duration modeling, Developed strategies for lexical explosion issues (i.e., handling enclitics in spanish), developed basic tools (inflectors, de-inflectors, etc.). From December 1993 to September 1995 (1 year 10 months) PhD, ECE @ Carnegie Mellon University From 1995 to 2000 MS, ECS @ Boston UniversityBS, ECE @ Tecnológico de Monterrey Juan Huerta is skilled in: Business Intelligence, Speech Recognition, Research, Natural Language Processing, Text Mining, Machine Learning, Data Mining, Artificial Intelligence, Pattern Recognition, Computer Science, MapReduce, Optimizations, Algorithms, Hadoop, Analytics

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In a nutshell

Juan Huerta's Personality Type

Introversion (I), Intuition (N), Thinking (T), Judging (J)

Average Tenure

3 year(s), 9 month(s)

Juan Huerta's Willingness to Change Jobs



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Juan Huerta's Social Media Links

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