LINE Wallet & Fintech - ML/Data Scientist

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Cloud computing, Scala Programming, Machine learning techniques, Data science techniques, MATLAB Programming, PyTorch, TensorFlow, R Programming

Job Description

• provides customized recommendations to users in various Fintech service areas such as securities, assets, and payment, as well as lifestyle services such as coupons, membership, and points.
• In order to provide suitable services and contents to users, we not only create a recommendation model based on various data, but also
• discover features necessary for user analysis and recommendation, and perform growth hacking through experiments based on this.
• We are waiting for those who will work together to create a recommended platform that can change the lives of users globally.

Responsibilities

• Application of design and development services of various AI technologies and recommendation models
• Discovering various features required for recommendation models and verifying their effectiveness
• Design and conduct various experiments for service growth
• Planning and verification of performance comparison and improvement based on the recommendation result
• Building ML Pipeline and Deploying Services
• Data extraction, analysis, and modeling from log data

Qualifications

• DA/DS/ML and a master's degree or higher in an adjacent field, or equivalent work experience
• Those who have work experience in planning user recommendation service and applying it to products
• Those who can design experiments based on data and derive insights through them 
• A person who can collect various data necessary for recommendation and use it for service 
• Those who can improve the recommendation service through statistical and logical analysis and reasoning 
• Technical Keywords Python, Pytorch, R, Tensorflow, Spark, SQL
• Those who have no grounds for disqualification for overseas business trips and work

preferential treatment

• Recommended model and pipeline Hands-on experience
• Experience in building data pipelines or MLOps
• Those with a strong understanding of the latest technology trends and various analysis models
• Those who can work in a foreign language (at least one in English or Japanese)