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Hong Kong

    Data Science Trainee - Hong Kong, 香港 - China CITIC Bank International Limited

    China CITIC Bank International Limited background
    全职
    描述

    Key Responsibilities:

    • Develop and build customer labelling models and data pipeline for digital customer engagement
    • Develop/test AI and advanced analytics models for digital customer engagement, targeting and personalization and support project execution
    • Develop/test data feature engineering process on big data platform like spark platform/Kafka
    • Design and develop quantitative models for data management improvement

    Requirements:

    • Postgraduate or 3rd year Undergraduate student in Quantitative disciplines (Computer Sciences/ Engineering/ Statistics/ Math / Economics/Business Analysis/Data Science/Math)
    • Knowledge/strong interest and sense in digital and latest technologies
    • Knowledge in big data technology like Spark and Kafka is preferred
    • Programming experience with Python, R and SAS is preferred
    • Good analytical and problem solving skills
    • Passion and curiosity for data analysis and technology
    • Self-motivated and proactive mindset
    • Quick learner and adopt new changes
    • Good command of written and spoken English and Chinese (Cantonese and Mandarin)

    For more details about career opportunities with the Bank, please visit our website Please apply with full resume stating current and expected salaries.

    Personal data collected will be used for recruitment related purposes only. Applicants not invited for interview within 6 weeks may consider their applications unsuccessful. However, applicants may be considered for other suitable positions within the Group for a period of not more than 2 years. Personal data will be destroyed at any time after 3 months.

    China CITIC Bank International is committed to being an equal opportunities employer and intends to provide a work environment free of unlawful discrimination or harassment. All employment decisions will be made in a non-discriminatory manner.



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