I recently completed the Metis data science boot camp in New York City. Metis is a rigorous 12-week immersive program that combines theory, machine learning and programming with project experience. By the end of the program, I had hands on experience with predictive modeling across five projects. Metis was a great way to sharpen the analytical skill set I had gained in my two previous jobs.
Before Metis, I worked for SocialCode, a social ad technology company. SocialCode helps Fortune 500 companies leverage data from social media platforms such as Facebook, Twitter, Pinterest, and SnapChat to better understand their customer base and improve return on digital ad spend. My job ranged from optimizing ad spend for a given client to identifying industry trends across the social platforms using SQL and Python. While I was with SocialCode, I was able to use my skills in computer programming and statistics to identify inefficiencies in a $7 million Facebook ad campaign that had previously been over looked. Ultimately, I improved the client’s cost per purchase by 38%.
Prior to joining SocialCode, I worked for Mu Sigma, a management consulting firm. Mu Sigma works with Fortune 500 companies to help them leverage big data in order to improve decision making. While working for Mu Sigma, my client was Walmart. My projects ranged from identifying areas of growth within the clients fuel station customer base to implementing cost reduction measures in the clients pharmacy division by identifying price spikes on various drugs. As a result of my analysis, the client saved an estimated $100 million in drug costs that otherwise would have been lost to unidentified price spikes.