Carlina Kim

Determined, analytical and a great communicator- Carlina values sending message and storytelling through data. With her expertise in data science and background in environmental science her niche skills gives her an advantage to excel in the field of environmental data science. She has been published for her research in major publication companies such as Forbes, HBR, and Washington Post.

Visier, Vancouver, BC, Canada May 2021 – Feb 2023

Data Scientist

• Developed our quarterly released product on industries KPI’s benchmark metrics with a 12% increase in number of new metrics generated reaching our 100M Benchmarks goal. 
• Initiated and created new economic indicators for major financial institution clients tying in employees with economics while improving our pipeline to expand data querying capabilities and increased our research database by millions of more data.
• Integrated new codebases with our research pipeline infrastructure and researched anonymized data for people analytics insights (i.e. Resignation Wave, Turnover Contagion, and Ethical Hiring). Led and published 5 research reports and blogs that received recognition from world class media companies (Forbes, Fortune Magazine, WSJ) saving $1.07M on marketing.
• Mentored 3 successful Co-ops students.
• Able to move and be promoted from Intern, Data Scientist l to Data Scientist ll in of 20 months.
• Tools: Python, Jenkins, AWS S3 and Sagemaker, IntelliJ, iTerm2, Bitbucket, Jira

NLP Data Scientist

• Designed a NLP Chatbot model for breast cancer patients that aims to provide mental health and side effects educational resources using advanced machine learning methods such word embeddings, deep learning models, and intent classification.
• Tools used: Python, Flask, APIs, TensorFlow

Data Analyst

• Consulted solar energy companies on current best practices, data quality validation using data science, measured KPI metrics through visualizations and introduced team to data science techniques such as Topic Modelling.
• Accelerated the data flow efficiency for GoFor by automating manual tasks in Purolator’s driver’s data management pipeline involving shipment details, shipment sizes, Driver’s ID and pay using data wrangling in Python and VBA Macros. 
• Training and webinars provided in data cloud systems and renewable energy sector through access to conferences and workshops. 

Air Quality Data Analyst - Internship

• Constructed time series analysis on ground-level ozone of Metro Vancouver from air quality stations by analyzing seasonality, intra-annual variations, and decomposition trends; used to bring insight on background stations 2010-2017 pollutant data and tracked whether ozone and precursor pollutant levels are meeting required ambient air quality objectives.
• Analyzed comparisons from historical results using statistical methods to understand how pollutants related to background ozone behave and predicted future trends using forecast in R. 
• Authored a data visualizations summary report (ggplot) to support the planned renewal of Vancouver's Regional Ground-Level Ozone Strategy and proposed findings to members of Environment and Climate Change Canada and Metro Vancouver.

Meta-Analysis Researcher

• Integrated a meta-database by applying meta-analytical methods such as data compiling, cleaning, and wrangling using R to various agricultural primary experimental datasets to improve efficiency by drawing comparisons of common cropping mechanisms; data product to be implemented on web-based application used by farmers, policymakers, and academics to guide food and agriculture policy and decision-making.

Administrative and Communications Assistant

• Supported graduate office team and worked cross-functionally with UBC sectors such as the Finance department, coordinated meetings by co-managing the program’s communication, and assisted PhD candidates with conducting research studies.
• Improved engagement on weekly seminar events with upgraded social media platforms and increased audience participation.

University of British Columbia, Vancouver, BC, Canada 2019 - 2020

Master of Data Science (MDS), (GPA: 4.0) 

• Topics: Algorithms & Data Structures, Data Wrangling / Manipulation & Visualization, Machine Learning (ML), Natural Language Processing (NLP), Statistics, Databases and Data Retrieval, Software Collaboration, 
• Languages & Softwares: Python, R, PostgreSQL, JupyterLab/Notebook, Github, AWS

Bachelor of Science (B.Sc.), Environmental Sciences (GPA: 3.7)

McGill University, Montreal, QC, Canada 2013-2014

Faculty of Arts & Science