Brian Kim

Brian Kim, a data scientist, has a strong desire to work in the marketing field. As a data scientist with a focus on marketing science, he has applied a variety of machine learning and statistical models to a wide range of media data in order to distinguish "signal" from "noise" and identify patterns. Programmatic advertising and social media data have been among the data kinds that have been collected.
Starting Out in the Insurance Industry
At Healthy Bytes, a New York-based healthcare business, Kim began his data science career in 2017 by performing exploratory data analysis on insurance claim data, which he learned through the use of the Python programming language. Aside from that, he created an Extract-Transform-Load (ETL) pipeline to obtain data from the document-based database MongoDB. After parsing the data, he developed visuals for company and management reports using Tableau software and Python programming language. To assure compliance with Health Insurance Portability and Accountability Act (HIPAA) regulations, Kim also applied machine-learning algorithms to health insurance data. In the course of carrying out all of these responsibilities, he reported directly to the company's CEO and CTO.

Data Science is the study of data.

Following his engagement with Healthy Bytes, Kim spent a brief period of time working for Metis, a data science and analytics organization based in New York. He worked at Metis, where he developed proprietary datasets and used machine learning to a variety of applications.

One of these assignments was the identification of mobile click-fraud on mobile devices. Kim employed machine-learning algorithms to accurately identify fraudulent clicks on a company's mobile ad network, and the results were published in Scientific American. Kim was able to wrangle and resample a large-scale data frame by utilizing the Apache Spark analytics engine hosted on Amazon Web Services (AWS) (AWS). Aside from that, he created at least 40 distinct features and modeled discrete data using XGBoost and GBM, which allowed him to achieve an 88 percent recall rate.

Kim began working at Metis in March 2018 and has since earned a certification in data science and machine learning. (He also has a Google Analytics certification, which is useful.)

Marketing Data Science is a term that is used to refer to the study of marketing data.

Kim worked as a data analyst at Media Assembly, a New York-based integrated media firm, where she pulled insights from television, search, social media, and programmatic channels utilizing SQL, Python, and R languages for a variety of different client vertical categories. It was his responsibility to submit the outcomes of a multi-touch attribution model to the company's senior management in order to improve the company's media optimizations. As part of his work, he redesigned existing media mix models (MMMs) in order to improve the efficiency and measurement of digital marketing campaigns.

The creation of client conversion, revenue, and long-term value (LTV) models by integrating relevant key performance indicators (KPIs), such as cost-per-click, clickthrough rates, and impressions, in order to maximize the allocation of client media budgets was another accomplishment Kim achieved while working at Media Assembly. Kim once again used Tableau to create visuals, which in one instance assisted a major pharmaceutical customer in increasing the effectiveness of their television ad campaigns.

Kim worked with a data engineering team at proprietary agency DMP to redesign ETL methods in order to improve the accuracy and completeness of the company's data collecting. He also collaborated on a "Point of View" document for the agency, which covered a wide range of topics, including the possible impact of GDPR/CCPA legislation and changes to third-party cookie policies.

Kim has frequently described the technical elements of multiple data-science initiatives to a wide range of non-technical stakeholders, including strategy, planning, and investment teams, in a straightforward and understandable manner. Kim took a risk by project managing several analytics deliverables and insisted that data scientists and data analysts adhere to strict timelines in order to ensure that projects were completed on time and with accuracy.

Donating to Charities

Kim currently resides in the New York borough of Queens.

In addition to data science and digital marketing, Kim has a strong interest in the arts, design, music, and online learning opportunities. In recent years, he has given significant contributions to two organizations in which he deeply believes: Planned Parenthood and Khan Academy.

Planned Parenthood, originally known as the American Birth Control League (until changing its name in 1942), is a non-profit organization that provides reproductive health care services throughout the world, with a focus on the United States. In addition to operating more than 600 health clinics in the United States, the group has affiliates in 12 other countries across the world. The organization has a total of 159 affiliates (including medical and non-medical). Abortion is the most common service provided by Planned Parenthood, which is the nation's largest supplier of reproductive health services overall. Planned Parenthood, in addition to providing direct health care, is involved in reproductive technology research and is an advocate for the extension and protection of reproductive rights. According to research, maternal death rates increased in a number of local communities after Planned Parenthood facilities were closed as a result of the closures.

Khan Academy is a nonprofit online education organization situated in California that was founded by American educator Sal Khan. In addition to more than 6,500 educational video lessons and tutorials that individuals can view and download to educate themselves on a wide variety of academic topics, Khan Academy maintains a number of free online tools that support the more than 6,500 instructional video courses and tutorials. Initial emphasis was placed on math and science courses, but the company's offerings have grown to include a wide range of topics, including test preparation and technical issues, such as computer coding. Organizations that support nonprofits have made analog versions of the Academy's videos available in rural areas of Latin America, Asia, and Africa, along with a variety of subtitled translations. In addition, the Academy has developed unique practice exercises and tools for educators who wish to include its videos into their lesson plans.