Think Big Analytics has been helping innovative companies Think Big with big data since 2010. They were acquired by Teradata in 2014 as the world’s first pure-play big data services firm. They’re big thinkers about big data – harnessing its power, unlocking its potential, managing the complexities, mastering the possibilities and synchronizing myriad technologies so businesses can move from insight to action. Their passion is deep data science and advanced data engineering that’s focused on generating business value from big data.
Jack McCush is the Principal Data Scientist at Think Big. In this role, he is often leading Data Science projects for organizations that are either leaders in the digital space or undergoing digital transformations. Much of the financial benefits of Data Science are realized by organization incorporating new and varied digital data and emerging technologies with their legacy data & analytics infrastructure.
Jack will be speaking at the Marketing Metrics and Analytics Summit on Sept 26-27, 2017 in Chicago, IL!
Listen to our Interview with Jack McCush
Jack has helped define, build, test and deploy solutions in the area of Search, NLP, Text Classification, Named Entity Recognition, Image Classification, Recommender Systems, Customer Segmentation and Uplift Modeling. These capabilities improve the productivity of almost any Data Science team, however, some of Jack’s biggest successes come when he has helped his clients automate the last mile of Data Science.
Jack has helped his customer build model publishing and management frameworks and integrate them into the data science workflow. The days of waiting weeks or months for a model to be put into production is in the past. These frameworks also incorporate model performance monitoring and automated retraining to allow the Data Scientist to be at maximum productivity.
Think Big Analytics provides enterprise customers with
- Big data strategy – roadmaps that prioritize the possible to create more value, and much sooner than you would expect.
- Data engineering – solution design and delivery aligned to core business objectives.
- Data science – deeper questions and new approaches to solve existing problems and seize new opportunities.
- Managed services and training – management and optimization of big data systems to improve performance; plus training to increase organizational adoption
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