Data Science Intern - University Students - FinLab job in Atlanta at McKinsey & Company

Who You'll Work With

You will work in our Atlanta, Chicago, Dallas, or Waltham office with our FinLab team for ~10 weeks.

You will work with analytics colleagues, software engineers and architects, McKinsey consultants and clients to carry out complex analyses, build statistical and machine learning models, and develop actionable recommendations for a wide range of strategic topics in industries such as financial services, real estate, retail, and public sector.

McKinsey works with clients in many industries to build custom software solutions that combine deep industry expertise, strategic insights, and AI/ML analytics to solve high impact business problems.

What You'll Do

You will perform statistical data analyses, data mining and optimizations using multiple tools and techniques to get insights from large complex data sets.

In this role, you will conduct hands-on rigorous quantitative analysis including getting the data, cleaning it (when necessary/relevant) and exploring it for accuracy. Additionally, you'll deploy statistical modeling and optimization techniques most suited for the business problem (using Python, SQL, and/or other relevant tools).

For ~10 weeks over the summer, our full-time internship program offers undergraduate students and eligible graduate students first-hand experience with digital and analytics consulting at McKinsey. You will participate in an introductory training program, as well as a range of social activities to get to know your office and the firm.

Qualifications

• Undergraduate university student in a STEM related field (e.g. data science, computer science) with expected graduation date between December 2023 to June 2024; Master's student completing the first year in a non-business, 2-year Master's program with less than 2 years of work experience
• Strong analytical and problem-solving skills paired with the ability to develop creative and efficient solutions
• Ability to work collaboratively in a team environment and effectively with people at all levels in an organization
• Deep understanding of statistical and predictive modeling concepts, machine-learning approaches, clustering and classification techniques and recommendation and optimization algorithms
• Experience in two or more programming languages (Python, SQL) Ability to easily understand the complex algorithm and logic to process data
• Experience working with a large volume of data with ability to solve performance issues
• Basic business intuition and clear expertise in analyses with the ability to describe analytic processes, including when and why specific approaches are favored
• Strong command of English language (both verbal and written)