Data Scientist – Advanced Analytics
- University degree in (applied) industrial engineering, mathematics, physics, computer science, or related natural sciences
- Track record in operations-oriented analytical and methodological data modeling (structured and unstructured machine and non-machine based) to generate insights that could not be gained through conventional techniques
- Previous experience working with numbers, statistics, and analytics/software solutions (e.g., SPSS, Statistica) as well as optimization software (e.g., GAMS or AMPL)
- Experience in analyzing complex datasets and building mathematical models, also in practical context
- Comfortable with explaining complex analytical and technical content to various audiences, ranging from operational specialists to members of top management
- Previous experience working with programming languages (e.g., Python, R, SAS) and data management systems (e.g., Hadoop, MySQL)
- Demonstrated aptitude for analytics
- Proven record of leadership in a work setting and/or through extracurricular activities
- Ability to work collaboratively in a team environment
- Fluent in English and the language of the local office
Who You'll Work With
You will work in either Dusseldorf, Paris, or Madrid with our Operations Analytics team as well as with the global group of analytics experts.
You'll work closely with our clients and colleagues, bringing together industry, functional, and analytics expertise to develop a comprehensive understanding of trends, identify the biggest opportunities, as well as anticipate and address potential risks.
What You'll Do
You will apply your methodological skills in operations research to devise innovative approaches for our clients.
This includes mapping, extracting, cleaning, organizing, and preparing terabytes of complex data for analysis in order to model and manipulate large sets of data from a wide variety of clients to glean business insights. You will leverage our proprietary analytic tools as well as design and prototype client-facing dashboards, operational models, and other applications.
Advanced analytics techniques open up a whole new world for operations topics. The use of big data and machine learning is a true revolution, as it increases, for example, productivity through predictive maintenance or production throughput. Advanced analytics techniques can also be used for network configuration, dynamic modeling in supply chains, or to gain data-driven insights into customer behavior.
Meet Some of McKinsey's Employees
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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