Data Scientist - China Innovation Hub

Key Skills

Python Programming, PySpark, SQL, Apache Airflow, Databricks, Kedro, AWS, Google Cloud Platform (GCP), Azure, Scala Programming, RDBMS, PostgreSQL, Amazon RedShift, Teradata, Snowflake, NoSQL, Apache Cassandra, Neo4J, Titan, MongoDB

Job Description

Who You'll Work With

You will join our Beijing, Shanghai, or Shenzhen office and be part of our Analytics team within the China Innovation Hub. You will join a team delivering world-class data applications to generate lasting impact for McKinsey’s notable clients in Greater China and beyond.

Analytics is a rapidly growing practice within McKinsey’s Greater China office and we work much like a start-up within our larger firm. We provide distinctive end-to-end services to our clients on a wide variety of innovation related topics, including digital implementation, new digital business setup, big data analytics, digital / physical product design, digital marketing, and digital center for operations excellence etc.

You’ll be actively cooperating with data scientists and digital consultants to incorporate clients’ requirements and impactful analysis into our data products. You’ll also be an expert in data engineering and advising relevant people at the firm on technical aspects of analytics engagements.

What You'll Do

You will carry out complex data analysis and modeling, and will proactively work with our consultants to support clients in a variety of industries by creating complex mathematical models and analytical approaches that power a critical business .

In this role, you will develop prototypes / analyze data sets in R, Python, Tableau, Alteryx etc., conduct statistical analyses, and evaluate large data sets.

Your 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.

In project ­work and in exchanges with colleagues, as an analyst you 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 being a thought partner to the business on shaping the problems as well as the solutions. You will help clients to translate big ideas into reality with delivered insights. You will innovate new tools and techniques in an encouraging environment and apply your understanding of insights in a real business setting.

Lastly, you will also get exposure 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 trying to retain the best talents, or an auto OEM reducing leads generation cost.

Qualifications

• Degree from a reputable university with quantitative focus, e.g. economics, mathematics, statistics, physics, computer science, operational research, financial engineering; advanced degree with quantitative project experience a plus
• 5+ years of data analytics related work experience in a leading company in the industry
• Data science experience focused on a specific industry e.g., financial service, retail, internet etc., preferred
• 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
• Strong analytical and problem-solving skills paired with the ability to develop creative and efficient solutions, with tolerance to deal with bad quality data
• Ability to translate scientific insights into product decisions and work streams
• Good people skills, team orientation, quality-oriented, highly committed and professional 
• Excellent communication skills in English and Mandarin Chinese (both oral and written)