Machine Learning Engineer
Data Intelligence Office is dedicated to leveraging data science and machine learning to provide solutions that enhance the various functions of Rakuten Travel. From product development to marketing, sales, advertising, and quality control, we use data-driven insights and predictive analytics to drive innovation and deliver measurable results.
Why We Hire
We are currently seeking talented ML engineers to join our team and take on the responsibility of optimizing Rakuten Travel's marketing activities. In a rapidly changing online travel industry, it is crucial that we provide our customers with a more personalized and tailored experience. As such, we are constantly on the lookout for enthusiastic data scientists who can help us deliver the best possible value to our customers. Additionally, we offer a supportive environment where we analyze user logs and run various experiments to continuously improve our products through iterative development.
As a member of our team, you will work closely with business side to understand their challenges, collaborate with data engineers and front-end engineers, and deliver solutions that optimize Rakuten Travel's product offerings. Specifically, you will be responsible for projects such as item recommendation, user targeting, image optimization, and NLP tasks utilizing user reviews. In this role, you will have the following key responsibilities:
- Collaborate with business side to define project requirements.
- Develop detailed dev specifications.
- Build and deploy ML models via APIs.
- Design and execute experiments to validate solutions.
- Conduct AB tests and bandit optimizations to compare different approaches.
- Evaluate experimental results using statistical tests to measure impact and effectiveness.
· Master's degree or higher in a quantitative field such as Statistics, Mathematics, Econometrics, Computer Science, Physics, Engineering, Bioinformatics, or a related field or equivalent practical experience.
· At least 3 years of industrial experience building machine learning/deep learning models, including those related to image processing, NLP, and other related fields.
· Strong proficiency in SQL and distributed system optimization, including tools like Spark, Presto, Hadoop, and Hive.
· Fluent in Python and able to effectively use it in data analysis and modeling.
· Demonstrated expertise in experimental design and statistical analysis, including experience with A/B testing, multi-armed bandits, and causal inference from observational data.
· Proven ability to work in a cross-functional team environment and collaborate effectively with other teams.
· Strong desire to stay up-to-date with the latest technologies and trends in the field of machine learning and data science.
· Proven experience in deploying machine learning systems to a production environment.
· Fluency in Japanese is considered a plus.
· A track record of publications in top international conferences, demonstrating expertise in the field of machine learning and data science.
|Location||Rakuten Crimson House, 1-14-1 Tamagawa, Setagaya-ku, Tokyo158-0094
(1 min walk from Futakotamagawa Station on the Denentoshi Line)
|Remote work||Partial remote|
|Working hours||9:00am - 5:30pm (Every Monday, work hours are from 8:00am to 4:30pm due to morning meeting)|
|Holidays||・2 days off per week (Saturdays, Sundays, and national holidays are holidays)
・10-20 days of annual paid vacation (the minimum number of days is the number of days granted after six months of employment)
・120 days off per year
In addition, year-end and New Year vacations, paid vacation, congratulation or condolence leave, maternity and paternity leave, etc.
*Once a year, you can take 9 to 12 consecutive holidays by using the long vacation (Success Vacation) system.
|Employee benefits||・Commuting allowance
・Employee pension insurance
・Workers' accident compensation insurance
・Retirement allowance system
Supplemental education and qualification support
・English learning support (in-house TOEIC(R) test IP test, English conversation, etc.)
・Career challenge system (challenge the department of your choice)
・Job return system (rehiring system for those who retired due to marriage, childbirth, nursing care, etc.), etc.
・Stock Option Plan
・Cafeteria system with three free meals
・LILO Club (preferential treatment at sports clubs, accommodations, leisure facilities, movie theaters, etc.)
・LILO Club (sports clubs, lodging, leisure facilities, movie theaters, etc.) (Running, mountain climbing, cooking, etc., part of the expenses paid by the company)
・Free English conversation lessons by native English speakers
・Support system for certification acquisition
・Qualification support system, etc.