Data Science & AI Department, under the Tech Division, leads the transformation of Rakuten by commercialization of Artificial Intelligence, Cognitive Computing and Machine Intelligence Technologies for Rakuten businesses.
With access to Rakuten?s ecosystem of more than 70 services, global businesses and technology expertise across Asia, Europe and the Americas, AI Solutions Incubation Section goal is to ideate, develop and provide transformative AI products in the fields of Commerce, Financial Services, Marketing and other Rakuten focus areas.
AI Solutions Incubation Section accelerates the adoption and impact of AI ML technologies via utilizing billions of consumer and industry data points accumulated within Rakuten?s ecosystem.
Exp Require : 5.5 Years – 7.5 Years
Masters/PhD in quantitative field (Computer Science, Mathematics, Machine Learning, AI, Statistics, or equivalent)
Industry experience in predictive modelling, recommender systems and data analysis
Solid understanding of foundational statistics concepts and ML algorithms: linear/logistic regression, random forest, boosting, GBM, NNs, etc
Previous experience, preferably in product company, in a ML or data scientist role and a track record of building ML or DL models
Experience using Python and ML libraries, such as scikit-learn, pandas, numpy, scipy
Experience handling terabyte size structured and unstructured datasets using distributed frameworks such as Spark, Hive
Familiarity with using data visualization tools
Experience working with GPUs to develop deep learning models
Ability to develop experimental and analytic plans for data modelling processes, use of strong baselines, ability to accurately determine cause and effect relations
Demonstrable track record of dealing well with ambiguity, prioritizing needs, and delivering results in a dynamic environment
Along with product managers, own the business outcomes/metrics which the data science model/algorithm drives
Strong written and verbal communication skills
Bonus Points for Experience with A/B testing