- 2+ years of hands-on data analysis experience
- Bachelor's degree in quantitative field like Computer Science, Engineering, Statistics, Mathematics or related field required. Advanced degree is a strong plus
- Advanced knowledge of data management tools including SQL/DBMS, MongoDB, Hadoop and/or other big data technologies
- Advanced programming skills in Java, Python, R, C++, C#, etc.
- Knowledge of statistical and data mining techniques (regression, decision trees, clustering, neural networks, etc.)
- Experience with data visualization tool is plus
- Exposure to online, mobile, and social data is a plus
- Intellectual curiosity, along with excellent problem-solving and quantitative skills, including the ability to disaggregate issues, identify root causes and recommend solutions
- Ability to independently own and drive model development, balancing demands and deadlines
- Strong people skills, team-orientation, and a professional attitude.
Who You'll Work With
You will work in Moscow as part of our Advanced Analytics team, partnering with consultants, clients and other colleagues.
Our Advanced Analytics teams bring the latest analytical techniques plus a deep understanding of industry dynamics and corporate functions to help clients create the most value from data.
What You'll Do
You will be a core member of McKinsey analytics platform team responsible for extracting large quantities data from client's IT systems, developing efficient ETL and data management processes, and building architectures for rapid ingestion and dissemination of key data.
Working on projects and exchanging experiences with your colleagues means you will face new intellectual challenges on a daily basis, while continuously building your methodological knowledge and skills. You will be exposed 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 railway determining optimal crew deployment, or a medical care provider understanding the main drivers for delays in surgery scheduling. In this role, you will be the point person in data architecture and management for our cloud platform and other high-tech initiatives.
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