Hello, my name is

(Reimark Mendoza)

I'm a Data Scientist based in Calgary specializing in analytics, data engineering, and AI. With a track record of successful data projects in the travel industry and freelance work in healthcare, HR, and environmental sustainability. Passionate about developing efficient ML and AI solutions that drive growth and unlock opportunities. Let's revolutionize your organization's potential. 🤓

01 / Methane Quantification Datathon Competition

As a lone participant, I have worked on this project that revolved around the development of a deep learning model that utilized infrared imaging data from GAO and AVIRIS-NG to detect and estimate methane emissions from point sources. This innovative approach showcased my expertise in applying advanced techniques to address environmental challenges and contribute to the sustainable management of methane emissions, a crucial aspect of mitigating climate change.

02 / Pasajob App Referral Fee Machine Learning Project (Client Work)

In collaboration with a talented group of data scientists on an impactful project. Together, as a team of five, we worked on developing a machine-learning solution for the Pasajob app, specifically focused on predicting the optimal referral fee for a given position. The objective of this project was to enhance satisfaction for the referrer, applicant, and employer. Through our data-driven approach, we aimed to optimize the referral fee. This project highlights my ability to work collaboratively, apply machine learning techniques, and drive positive outcomes for both the proponents

03 / Travel Itinerary Generator PH

As a Market Analyst for the Ministry of Tourism Philippines, I have worked on an exciting project centered around developing a personalized travel itinerary recommendation system for Region 4a of the Philippines. By harnessing the power of Natural Language Processing (NLP) and Network Analysis, our machine learning model takes user inputs and generates destinations and attractions based on a prompt.

04 / Solar Plant Regression Analysis

The objective of this project is to analyze a dataset containing information from two solar plants and to uncover relationships among the data features to give recommendations and inferences that would solve a business problem. The dataset consists of power generation data and weather sensor readings collected over a period of 34 days for each of the two solar plants.

01 / Goldspring Consulting Analytics Dashboard (Client Work)

As an experienced professional in the travel industry, I had the privilege of leading a team of five individuals for our capstone project during the Data Analytics Certificate program at Bow Valley College, Calgary, Canada. Our project centered around leveraging the extensive database of Goldspring Consulting and has identified patterns and devised effective strategies for increasing their market share in preferred hotels for business travel.

02 / SeeYouDoc App Customer Segmentation (Client Work)

SeeYouDoc, an innovative online consultation startup provides patients and physicians with a convenient and comfortable platform to conduct virtual sessions. My task was to delve into their extensive database using SQL and Python and unearth valuable patterns and insights that could be leveraged to enhance SeeYouDoc's services and elevate the overall customer experience.

03 / HR Turnover Rate Data Visualization

In this data analytics project, I have examined various variables such as employee demographics, performance metrics, job satisfaction levels, compensation packages, and other relevant factors. By leveraging the power of Tableau,  the visualizations effectively highlight the factors relating to the high turnover rate.

04 / World Health Organization Life Expectancy Data Visualization

As a data enthusiast, I enthusiastically embarked on a challenging project suggested by one of my mentors. The task involved working with data from the World Health Organization (WHO) and creating a dashboard visualization of life expectancy trends, with a specific focus on developed nations. The goal of this project was to develop a powerful dashboard that could be utilized by participants, policymakers, and medical practitioners worldwide, enabling them to gain valuable insights into the factors influencing high life expectancy rates in developed nations.