Only at McKinsey you will work on real-world, high-impact projects across a variety of industries. You will identify micro patterns in data that our clients can exploit to maintain their competitive advantage and watch your technical solutions transform their day-to-day business. You will experience the best environment to grow as a technologist and a leader. You will develop a sought-after perspective connecting technology and business value by working on real-life problems across a variety of industries and technical challenges to serve our clients on their changing needs. Surrounded by inspiring individuals as part of diverse multidisciplinary teams, you will develop a holistic perspective of AI by partnering with the best design, technical, and business talent in the world as your team members. While we advocate for using the right tech for the right task, we often leverage the following technologies: Python, PySpark, the PyData stack, SQL, Airflow, Databricks, our own open-source data pipelining framework called Kedro, Dask/RAPIDS, container technologies such as Docker and Kubernetes, cloud solutions such as AWS, GCP, and Azure, and more!

• Partner with our clients, from data owners and users to C-level executives, to understand their needs and build impactful analytics solutions • Contribute to cross-functional problem-solving sessions with your team and deliver presentations to colleagues and client • Translate business problems into analytical problems and develop models aimed at solving our clients and users problems and ensure they are evaluated with the relevant metrics • Write highly optimized code to advance our internal Data Science Toolbox • Add real-world impact to your academic expertise, as you are encouraged to write papers and present at meetings and conferences should you wish • Take part in R&D projects; attend conferences such as NIPS and ICML as well as data science retrospectives where you will have the opportunity to share and learn from your co-workers • Work in one of the most advanced data science teams globally

Your qualifications and skills • Bachelor's, master's or PhD level in a discipline such as: computer science, machine learning, applied statistics, mathematics, engineering or artificial intelligence • ~10 years of professional experience in applying machine learning and data mining techniques to real problems with copious amounts of data • The title will be determined through a comprehensive evaluation of professional experience and interview performance. • Ability to prototype statistical analysis and modeling algorithms and apply these algorithms for data driven solutions to problems in new domains • Knowledge in applying machine learning solution to real problems with complex and/or big amounts of data • Willingness to travel • Fluent in Korean and in English

• Programming experience (focus on machine learning): SQL and Python’s Data Science stack are a must; good knowledge of at least one big data framework (Pyspark, Hive, Hadoop) is a plus; R, SPSS, SAS (nice to have); Software Engineering is a plus • Experience deploying technology applied to business problems is a plus

For more details, please refer to the company website.