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Science of Data

Following his time at Healthy Bytes, Kim worked at Metis, a data science and analytics firm based in New York. He produced proprietary datasets and used machine learning for a variety of initiatives at Metis.

One of these projects was detecting mobile click fraud. On a company's mobile ad platform, Kim used machine-learning algorithms to precisely anticipate fake clicks. Using the analytics engine Apache Spark on Amazon Web Services, Kim was able to wrangle and resample a large-scale data frame (AWS). To get an 88 percent recall rate, he created at least 40 distinct features and modeled discrete data using XGBoost and GBM.

Kim earned a data science and machine learning certification from Metis in March 2018. (He also has a Google Analytics certification.)

Data Scientist

Brian Kim

Brian Kim is a data scientist with a strong interest in marketing. As a data scientist specializing in marketing science, he's used a variety of machine learning and statistical models to extract "signal" from "noise" in various sorts of media data. Programmatic advertising and social media data have been among the data kinds used.
Starting Out in the Insurance Industry
Kim began his data science career in 2017 with Healthy Bytes, a New York-based healthcare business, where he performed exploratory data analysis on insurance claim data using the Python programming language. He also created an Extract-Transform-Load (ETL) pipeline to get data from the MongoDB document database. For company and management reports, he used Tableau software and Python to parse the data and build visualizations. Kim also used machine-learning algorithms to analyze health insurance data in order to assure compliance with HIPAA regulations. He reported directly to the company's CEO and CTO while fulfilling all of these duties.

Brian Kim 的社群動態