Quantify and predict student interactions to identify under performing students
Train predictive models on manufacturing process time-series data to predict and prevent future faults
Use data science to identify the highest value sales targets
Train machine learning models to predict consumer purchase behavior to optimize CPG campaigns
Use data science techniques to auto-normalize and unify data for an organization focused on showing the impact of the governmental policy decisions on real estate values
Develop specialized natural language processing (NLP) models to extract and organize newly published web content for a digital PR firm
Use machine learning algorithms to extract and organize food product ingredients from 2 million+ product label images and classify products into 2,000+ categories
Build ETL (extract, transform and load) pipelines and create a realtime unified store of analytics ready data from sources including web, social media, and app servers
Develop an algorithm to transform 2.5 Tb of text for ~8.5 million unique products into a hierarchical taxonomy and unified naming convention
Analyze purchase history trends to determine the impact of discount campaigns on customer visits and purchases
Data engineering, analytics, and NLP to understand brand, consumer and market trends for pharma clients and more
Leverage computer vision algorithms for object detection and image classification to extract industrial asset information
Software engineering to translate time series data into actionable insights
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