Junior Engineer - Performance Lens null

What you'll do

You will have direct accountability for several key initiatives across the Global Growth Cube.

In this role, you will work closely with Performance Lens colleagues globally and be responsible for developing and managing machine learning-based solutions to forecast the growth of the asset management industry across different markets.

You will also work with colleagues to deliver other Python and Excel-based solutions for the Global Growth Cube and build out data frameworks that allow such solutions to scale.

You will be an active contributor in improving the code quality and usability of these solutions while working in an agile delivery model.

Who You'll Work With

You will be based in our Gurgaon, India office as a direct part of our Performance Lens team.

Performance Lens is a McKinsey Solution that manages the proprietary data of the Wealth and Asset Management practice and provides fact-based, actionable insights to improve asset managers’ business performance by combining industry-leading data, analytics, and tools with McKinsey’s deep asset and wealth management expertise.

The Global Growth Cube is a unique resource that brings together and reconciles hundreds of disparate public and private data sources and overlays McKinsey’s proprietary data from our Global Asset Management Survey to consistently size over forty asset management markets globally. Our investment in this knowledge asset is grounded in the belief that a highly granular and objective perspective on the industry is critical for helping asset managers make key strategic decisions, whether this is understanding the 'Granularity of Growth', guiding resource allocation, or providing an objective source for assessing market share.

Qualifications

• Bachelor's degree in computer science or related fields.
• 1+ years of experience working in a fast-paced, high-demand business environment.
• Prior work experience in building business algorithms/scenario planners/simulation engines to solve business problems is an advantage.
• Hands-on experience working with Python.
• Strong Excel, analytical, and data management skills.
• Ability to work across structured, semi-structured, and unstructured data, extracting information and identifying linkages across disparate data sets.
• Capable problem solver with a drive to identify and execute creative solutions.
• Ability and flexibility to manage multiple assignments in a dynamic, complex, and fast-paced environment.
• High level of attention to detail.
• Comfortable with ambiguity; strong sense of ownership and perseverance.
• Comfortable with working across a global team based in multiple geographic time zones.
• Business-level language skills and fluency in English.