Job Description

•  Bengaluru, Karnataka, India

Business Overview:

Rakuten is one of the largest internet services company globally and provides more than 70 services spanning eCommerce, finance, telecommunication, sports and much more to approx. 1.4 billion customers worldwide. Following the strategic vision “Rakuten as a data-driven membership company”, we are expanding our data activities across our multiple Rakuten group companies.

With hundreds of millions of members and trillions (yen) in spending from members Rakuten’s Membership enjoys un-paralleled eco-system of benefits and amongst the largest in the world. Our talented and driven team operates a portfolio of data and data science products and services that enable personalization and enablement of sciences at Rakuten.

Rakuten Institute of Technology (RIT) was launched in 2005 as the dedicated R&D organization for the Rakuten Group. RIT’s Customer Program builds deep customer understanding at all the steps in the Customer Journey with Rakuten to deliver scalable, repeatable data science solutions for Marketing and Customer Nurturing products.

Deep CDNA Research team builds universal customer models and applications, motivated by the recent success of pre-trained models in the language and vision fields.

Such models can be adapted to improve a diverse set of service solutions including recommendation systems, customer targeting solutions, and credit scoring functions, to name a few.

Responsibilities

• Experiment with state of the art deep learning architectures to improve customer models for downstream tasks such as credit scoring, fraud, marketing, etc.
• Develop strong relationships with Rakuten functional areas to identify best practices, solicit input/data, coordinate interdisciplinary initiatives, and gather support for recommendations.
• Areas of opportunity and influence execution of results via cross-functional participation to enable quick wins and continuous improvement.

Qualifications

• Masters/PhD in quantitative field (Computer Science, Mathematics, Machine Learning, AI, Statistics, or equivalent)
• 12+ years of industry experience in predictive modelling, recommender systems.
• Solid understanding of foundational statistics concepts and ML and deep learning algorithms: linear/logistic regression, random forest, boosting, GBM, NNs, etc
• Previous experience, preferably in product company, in building 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