Data Scientist - China Innovation Hub
- Excellent communication skills in English and Mandarin (both oral and written)
- Quantitative degrees from top universities (economics, mathematics, statistics, physics, computer science, operational research, financial engineering etc.) with outstanding academic results, advanced degrees with quantitative project experiences a plus
- 3+ years' data analytics related work experience in a leading company in the industry,
- Data scientists focused on a specific industry (e.g., financial service, retail, internet etc.) are preferable
- An analytical thinker and also be able to solve problems creatively
- Comprehensive computer skills with understanding of basic coding. Experience and knowledge of database and statistical software (Such as SAS, R, Python) and can work with large data sets,
- Deep knowledge about statistics and machine learning. Domain expertise preferred: attribution, segmentation, response modeling, churn, propensity, customer LTV, supply chain / logistics, geospatial inference, recommender systems, causal inference, forecasting, pricing, NLP or image processing
- Ability to scope and define data sets needed for specific use cases and identifying data gaps
- Ability to translate scientific insights into product decisions and work streams
- Good people skills, team orientation, quality-oriented, highly committed and professional
Who You'll Work With
You'll join our Shanghai office affiliated to the China Innovation Hub and work closely with our consultants as a Data Scientist.
China Innovation Hub (CIH) is a rapidly growing team within McKinsey's Greater China office. It provides distinctive end-to-end advice to our clients on a wide variety of innovation related topics, including digital implementation, new digital business setup, big data analytics, digital / physical design, digital marketing operations, and digital center for operations excellence etc.
What You'll Do
You will join the team as a Data Scientist to carry out complex data analysis and modeling.
As an expert in analysis and methodology, the Data Scientists will proactively work with our consultants to support clients in a variety of industries by creating complex mathematical models and analytical approach that power a critical business function. You will develop prototypes / analyze datasets in R, Python, Tableu, Alteryx etc., conduct statistical analyses, and evaluate large data sets. The work will be project oriented, and you will often be responsible for the entire analytical process – from task definition to the implementation and interpretation of results to the delivery to the client. In dialogues with McKinsey consultants and with clients, you will discuss the analytics results constructively, in continuous search of the best possible solution and algorithm.
The work is multifaceted and exciting, and you will gain insights into many industries and into management topics. In project work and in exchanges with colleagues, the Analyst will deal with new intellectual challenges daily as well as build industry and knowledge of methodology on an ongoing basis. A clearly defined and flexible career path will help you to continuously develop business skills as well as analytics (based on your interest).
Working with McKinsey as part of the China Innovation Hub provides you with challenging opportunities, including: a) Be a thought partner to the business on shaping the problems as well as the solutions; helping clients to translate big ideas into reality with delivered insights; b) Innovating new tools and techniques in an encouraging environment and apply your understanding of insights in real business setting; and c) Exposing to an enormous variety of topics across many different industries such as a world-leading bank figuring out how to best do its customer care across all of its channels, a fast growing internet company tying to retain the best talents, or an Auto OEM reducing leads generation cost .
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Danielle is one of the leaders of McKinsey’s business with retail and consumer clients. She oversees client projects and helps her teams and her clients utilize McKinsey’s resources.
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