Producing highly accurate Predictive Models in Social Data Mining can be a challenge. Feature Engineering using traditional methodologies can only take you so far. Trying to find that needle in a haystack when the subject matter is too domain specific or prone to ambiguity can require large investments to achieve accurate results. Through this presentation we will discuss methodologies used by Toyota’s Research and Development Data Science Team and share secrets of building highly accurate Predictive Models for Social data using innovative techniques for Feature Engineering applied on the Apache Spark and MLlib platform.