The primary focus of my employment at B-Stock as been managing a Product Recommender Project, which is aimed at providing clients with a daily curated list of auctions. I have implemented machine learning techniques in python to differentiate between relevant and non-relevant auctions to ensure clients receive the auctions most relevant to them in their daily list. I have analysed the algorithm performance and fine-tuned results to account for entire client base. I am currently coordinating with the marketing and IT teams to implement algorithm with a test group of clients.

I utilised SQL to manipulate and analyse transaction data at Fresh Encounter grocery stores. I provided insight to number of transactions per week using a customer card at specified locations.

I completed consulting project for a company called LumenServe, Inc. based in Texas, USA. I helped expedite LumenServe’s light tower data cleaning process using Python to increase the frequency of monitoring their client’s tower maintenance needs. I quantified the number unique contacts in LumenServe’s database to determine their potential client market.