I work in fraud prevention and after 10 years of working with complex data and I am just starting to use machine learning (with a lot of software that makes it

I work in fraud prevention and after 10 years of working with complex data and I am just starting to use machine learning (with a lot of software that makes it simple). I'd be hesitant to call myself a Data Scientist but have borrowed heavily so to speak. Thanks guys! As my abilities to work with data have grown I've been amazed at the power of some of the simpler statistical tools and that they aren't more widely used elsewhere. My top X list: - Statistical sampling to get a quick estimate. Most of the time a quick answer that is accurate to 10% is worth more than an 'exact' answer that takes a month. - Statistical process control techniques to monitor operational process. Stop focusing on the noise and let the system tell you when something is broken. - How to incorporate uncertainty into your models using Monte Carlo analysis to improve decision making. Our model projects that saving may be between negative $10M and $20M conveys more information than our model projects $10M in savings. - How to incorporate trend and seasonality into forecasts using Holt-Winters. - Use of split testing to know when you have a significant result.