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Eric Kim

Data Scientist / Researcher





Silicon Valley, CA

Bay Area, CA

Los Angeles, CA

  • LinkedIn Profile
  • Publications
  • GitHub

Hi, I'm Eric!


» About me: Passionate data scientist with a twist of exceptional soft skills. An experienced veteran at data-storytelling to non-technical audiences. 

» Special trade: Incorporate math, science, and philosophy to deliver both quantitative and qualitative predictions through machine learning.


Quick Links Below

2017 - 2018

Data Scientist (Contract)


‣ Build company dashboard from scratch using Google Cloud Storage, Riot Games API, and Elasticsearch. (Python, Kibana, and Lucene)

‣ Feature engineer Value for over 500,000 users with event tracking, product use, and improvement in gaming rank. (Python and Machine Learning)

‣ Create data analysis blog content using Tableau and Riot Games API to help gamers improve (SQL and Python)

UC Irvine School of Medicine

‣ Incorporate computer science, medicine, and humanities to challenge the status-quo of traditional medical research. (SQL, Python, R, and Medical Surveys)
‣ Team up with dietitians, social workers, nurses, medical students, surgeons, and directors to produce and predict the future of patient healthcare. (R/Python with Regression Analysis and Machine Learning)
‣ Report directly to the chief gastrointestinal surgeon and vice president of surgery. 
‣ Lead a team of researchers to continue making an impact in the field of medicine. 
‣ 3 medical publications out and more in progress.

2014 - 2017

Lead Surgery Researcher

2015 - 2016

Tutor Lead

CA Future Focused

‣ While being in the position of a lead researcher, managed a group of 8 tutors.
‣ Taught over 600 hours of chemistry, biology, and mathematics for regular, honors, advanced placement, and international baccalaureate high school students. 
‣ Motivated students to set short and long term goals for their academic careers and endeavors.
‣ Made a profound influence on private/public school students that were preparing for college.


University of California, Irvine

‣ Undergraduate career focused on applying law and ethics as a student of Philosophy. 
‣ Passionate about using major to change how surgeons interacted with patients inside and outside medical care. 
‣ Enrolled in ethics, statistics, and medical classes on top of regular coursework to be able to give quality advice to patients and surgeons on what was optimal to go through.
‣ Seized the rare opportunity to work directly with the vice president and chief of surgery. 
‣ Innovated a way to combine medicine, humanities, and computer science to medical research which allowed me to teach other fellow researchers how to take on my projects after graduation.
‣ Published 3 papers in medical journals.


Bachelor of Arts Degree

Philosophy, B.A.


Associate of Science Degree

Mathematics and Science, A.S.

Cypress College

‣ Goal after getting an associate's degree in mathematics and science was to help others through tutoring and consulting. 
‣ Took classes during the morning, tutored others during the day, and worked at Disneyland in the evening. 
‣ Transferred to a top-tier UC and awarded a scholarship from UC Los Angeles.



Deep Learning

Statistical Methods

Data Storytelling

Apache Spark




Machine Learning

Data Visualization



Medical Publications

Excel / Numbers


What are the benefits to online dating? Can't we just meet people in school, at work, or in public? Naturally, we don't all have the finesse to do that. Perhaps we are shy, not into office drama, or just not social enough. 


The benefit to online dating is that we can present ourselves in a wall of text without ever leaving our busy lives. How convenient! Also, we can filter out other users that don't meet our standards rather than asking uncomfortable questions in person. However, with online dating, there are downfalls to the benefits. What if people aren't honest and how do people get quality matches?


This analysis will try to answer and give suggestions to improve the online dating experience. The full paper and code can be found on my GitHub. (I highly recommend you take a look at this if you are interested in the science behind the data!)

Predicting Traffic Signs with Neural Networks

There's nothing more important than safety when you are driving a vehicle. Have you ever commuted to work, school, or a frequent place only to arrive with no recollection of what happened during your drive? Do you feel safe? I trust myself, so yes. But not always. The ability that we have to do such things comes from our brain being able to use past events to guide us to drive while continuing to learn as are aware of our surroundings. What we get used to are things like weather, traffic signs, motion, and other objects that we react to. (Hopefully) Our brain uses it to predict what we are likely to do, which could be simply driving to work while avoiding obstacles. However, what if one day, we weren't able to be entirely safe due to fatigue or another factor that our brain cannot simply react fast enough to?

Handwritten Digit Recognition with Convolutional Neural Networks

There's nothing more frustrating that waiting in front of an ATM during your lunch break to deposit a check. Many bank patrons today use a feature on their phones to deposit checks which uses their phone cameras. But just how accurate is it to be able to trust? Sadly, we don't have that information available but I would consider anything under 1% error to be excellent. Luckily to us, we can make a neural network to mimic what these apps use. In this project, I will develop a deep learning model to achieve a near state-of-the-art performance on the MNIST handwritten dataset. I'm going to use Keras with TensorFlow.

Recurrent Neural Network to Predict Stock Prices

We can use a neural network to use 5 years of stock data from Yahoo Finance to predict our current year's stock prices. This study is based on a paper from Stanford University.

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Consideration for Esophagectomy in Patients with Prior Bariatric Surgery

Bariatric surgery is frequently performed for the treatment of severe obesity. Esophageal cancer has been reported to occur in patients who had prior bariatric surgery. Due to the anatomic alterations associated with bariatric surgery, esophageal resection requires an understanding of certain technical considerations. This paper describes the technical considerations in performance of an esophageal resection in patients who had prior sleeve gastrectomy or Roux-en-Y gastric bypass.

Trends in Utilization of Bariatric Surgery

Utilization of bariatric surgery has changed dramatically over the past two decades. The aim of this study was to update the trends in volume and procedural type of bariatric surgery in the USA. Data were derived from the National Inpatient Sample from 2009 through 2012.

Long-term Results of Laparoscopic Bariatric Surgery - 10-year Outcomes: A Prospective Randomized Trial of Laparoscopic Gastric Bypass versus Laparoscopic Gastric Banding (Approved March, 2017)

Bariatric surgery is an effective option for the treatment of severe obesity and its related comorbidities. However, few studies have reported on the long-term outcome (>5 years) of bariatric surgery.

Conclusions were that bariatric surgery is an effective treatment for severe obesity with durable 10-year weight loss and improvement in comorbidities and quality of life. 

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