Data Analyst (Python) – Digital Solutions – SZ/HK
DESCRIPTION
A career in Information Technology, within Internal Firm Services, will provide you with the opportunity to support our core business functions by deploying applications that enable our people to work more efficiently and deliver the highest levels of service to our clients. Our Information Technology Generalist – Practice Support team focuses on managing the design and implementation of technology infrastructure within PwC, developing and enhancing internal applications, and providing technology tools that help create a competitive advantage for PwC to drive strategic business growth.
Responsibilities:
• Building and applying data analysis algorithms (data mining, machine learning, natural language processing, sentiment analysis, text mining, etc.) to analyze large amounts of data
• Designing, developing solutions leveraging big data analysis technology (Python,R,SAS, etc.)
• Leveraging analysis data platforms as needed and recommending and building new data solutions as required to exceed business requirements
• Emonstrating deep understanding of and ability to tech data science, concepts, tools, features, functions and benefits of different approaches to apply them.
Requirements:
Bachelor in Computer Science/ Engineering/ Statistics/ Actuarial/ Applied Mathematics/ Business Analysis/ Data Science or other relevant discipline;
Has deep understanding and some practices of the System Implementation, Big Data, Machine Learning, Deep Learning, NLP, and other technical related concepts;
Coding experience in software like Python is a MUST. SAS, R, etc. would be ideal but not a must;
Have the python develop experience more than 1 years.
Experience in using packages such as pandas, numpy, sklearn and familiar with ML models like GBDT and xgboost would be a plus;
Familiar with industry dynamics of data big data analysis, equipped with various technical knowledge of data processing and relevant skills
Excellent communication and presentation skills;
Fluent English and Chinese.
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