Data Scientist - Operations

Job Description

Who You'll Work With

You’ll be joining the Boston, Chicago, New York or Silicon Valley office, and working with McKinsey’s Operations practice. Our Operations practice assists our clients in solving complex operational challenges. Blending strategic thinking with hands-on practicality, our teams of consultants and experts work to develop and implement operational strategies that solve our clients' most critical problems.

As part of our Operations practice, our Analytics team combines deep strategic and business insight with world-class technological and operational capabilities. Operations analytics helps solve problems in optimization, forecasting, and simulation - not only to improve the design of physical systems, but also to address management infrastructures and employees' attitudes and behaviors, so that clients are able to lead change independently.

What You'll Do

You will shape the future of what data-driven organizations look like, drive processes for extracting and using that data in innovative ways, and create new lines of thinking within an infinite number of clients and situations.

In this role you will apply your methodological skills across our operational service areas--supply chain, product development, manufacturing, etc.--to devise creative approaches for our clients in areas such as inventory management, predictive maintenance, or logistics network design. You will apply and advise on state-of-the-art quantitative tools and modeling techniques in order to derive business insights, solve complex problems and improve decisions.

Lastly, you will review, support, and inform the day-to-day analytics requirements of clients' key operational procedures while continually improving the impact of these processes.

Qualifications

• Bachelor's degree in operations research, computer science, engineering, applied math, quantitative social sciences, or related field
• Experience in predictive analytics, machine learning, and/or optimization
• Fluent in one or more programming languages (R, Python, C++, etc.)
• Demonstrated analytic and quantitative skills
• Strong intrinsic problem solving skills, ability to structure and solve problems and conduct and interpret analysis independently
• Skills to communicate complex ideas effectively
• Willingness to travel up to 80%