Data Scientist | Temporary Work From Home  

Join the no. 1 global South Korean e-commerce platform, where talent and creativity are valued. Advance professional development and learn consistently in an outstanding and enjoyable working environment. Showcase your skills and innovation. Be a part of our growing team of local IT professionals and experts from South Korea.

Why join us?

• HMO + 2 dependents upon employment
• Annual salary increase
• Allowances
• Paid vacation and sick leave of up to 15 days
• Training and Development Budget
• Team buildings
• Collaborate with Korean IT Professionals
• Value Work-Life Balance
• Opportunities for Career Growth and Development

Responsibilities

• Research about a given topic and related commercial products
• Acquire, explore, clean, and transform market data which might include web scraping, writing scripts for ETL and post-processing, and wrangling using R/Python
• Design data processing workflow based on business requirements
• Conduct statistical analysis and form visualizations to extract useful insights from a given dataset
• Research, train, modify, tune, and evaluate statistical/machine learning models
• Report results, insights, interesting findings, and updates
• Exert efforts to improve the performance of a given model
• Form prototypes, APIs, and SDKs to make the formed models usable to others
• Work closely with developers and data architects, both in local and overseas offices

• Proficiency in data handling in Python / R
• Self-motivated, able to work under minimal supervision
• Passionate about data science/analysis and research
• Able to work from home (Temporary)

Preferences:

• Passionate about data science and research
• Relevant work experience or having an advanced degree in the quantitative domain
• Desire to continuously acquire new knowledge in data science, business domain, and relevant technologies
• Values collaboration and has good communication skills
• Self-motivated, able to work under minimal supervision
• Proficient in data handling using R/Python
• Has strong knowledge in statistics and data analysis with experience in machine learning techniques for regression, clustering, classification, dimension reduction, natural language processing (NLP), computer vision/image processing, etc
• Experience in using different libraries for handling data and modeling such as pandas, NumPy, scikit-learn, PyTorch, TensorFlow, Keras, OpenCV, Pillows, etc.