Data Science Intern - McKinsey Analytics/Quantum Black

Key Skills

Python Programming, SQL, Machine learning techniques, NumPy, Pandas, TensorFlow, Scikit-learn, R Programming, PySpark, matplotlib, Julia, Gurobipy

Job Description

WHO YOU'LL WORK WITH

You will be part of our very dedicated and collaborative Advanced Analytics team in one of our German Advanced Analytics Hubs for three to six months and you will work on exciting projects from all industries. We work closely with clients and content professionals to embed analytics solutions, expertise and capabilities into our client's organization. By combining strategic and business insights with the latest analytical techniques, we help our clients derive maximum benefit from data and solve critical problems in a data-driven way.

What we offer:

• Diverse, cross-industry application possibilities in the context of advanced analytics
• Working in an international team at locations worldwide and in our German Advanced Analytics Hubs
• Training and support from experienced colleagues and at the same time interaction in a rapidly growing young team
• Inspiring and collegial environment of highly qualified employees from the fields of mathematics, physics, statistics, computer science, data science and engineering
• Participation in our regular international exchange of ideas.

WHAT YOU'LL DO

As part of this internship, you will support our specialists who, with the help of advanced analytics methods, develop solutions for the challenging problems of our clients - from conception to modeling to handover to implementation.

You use your knowledge of mathematics, statistics, data science, machine learning or optimization to derive important insights for and with our clients from a wide variety of industries. You contribute your expertise in interdisciplinary teams consisting of consultants, technical experts and data scientists. You work on site with clients in Germany, Europe and optionally worldwide and communicate your solutions both in the team and to the clients.

QUALIFICATIONS

• At least a bachelor's degree in (business) mathematics, statistics, machine learning, data science, physics, operations research, computer science or a related subject 

• Secure communication in German and English

• Experience in one of the following areas: statistical modelling, machine learning, mathematical optimization or process simulation

• First practical experience in applying advanced data science methods to real data in a business context

• Confident command of a programming language (e.g. Python, R, SQL or related languages)

• Basic knowledge of some typical frameworks, eg NumPy, pandas, scikit-learn, TensorFlow, PySpark, matplotlib or gurobipy

• In addition, experience in the use of gradient boosting, random forest, support vector machines, deep learning or alternatively in formulating and solving optimization problems with Gurobi, CPLEX or CBC or in the use of simulation software such as Anylogic or Arena

• Ideally, additional initial knowledge of big data infrastructure and cloud-based analysis tools such as AWS, Azure or Google Cloud