- MSc or PhD degree in a discipline such as computer science, machine learning, applied statistics, mathematics or engineering; BSc in AI or machine learning will be considered
- 5+ years of programming experience in Python is essential; other languages (e.g. R and SQL) are beneficial
- Ability to manage and query large databases including setting up and maintaining gigabyte to terabyte size databases of customer data, performing data integration, manipulation, and querying, and provide data mining and analytical support
- Strong understanding of advanced analytics or machine learning concepts for customer analytics including segmentation, cluster analysis, consumer behavior, pricing analytics, customer insights, etc.
- Intellectually curious and enjoys problem-solving, requirement gathering and recommends solutions
- Driven by numerical or statistical approaches
- Thoughtful and comfortable communicator (in person or on paper), to facilitate discussions and conduct training
- Ability to thrive in a flexible and collaborative environment
- Ability to work on more than one project at a time
- Flexible to travel for work, across Asia (may/may not include 50-70% of travel in a year)
What You'll Do
You will assist McKinsey clients through conducting the quantitative analysis across the spectrum of marketing and sales, including segmentation, propensity modeling, CLM, digital marketing, media mix modeling and pricing analytics.
You will conduct deep analytics on client and external data, playing a significant role in team problem solving through the findings and insights from analysis. You are expected to advance McKinsey’s overall knowledge base by providing analytical rigor and problem solving to our proprietary knowledge investments.
As a Data Scientist, you will also focus on developing new analytical approaches and techniques. You will operate as part of a wider firm community, supporting the development of both the analytical group as well as greater understanding of analytics and results in the consulting population.
You will work on the frameworks and libraries that our teams of data scientists and data engineers use to progress from data to impact. Watch our Protocols series video tutorial. You will guide global companies through data science solutions to transform their businesses and enhance performance across industries including healthcare, automotive, energy and elite sport.
- Real-World Impact – No project is ever the same; we work across multiple sectors, providing unique learning and development opportunities internationally.
- Fusing Tech & Leadership – We work with the latest technologies and methodologies and offer first class learning programmes at all levels.
- Multidisciplinary Teamwork - Our teams include data scientists, engineers, project managers, UX and visual designers who work collaboratively to enhance performance.
- Innovative Work Culture – Creativity, insight and passion come from being balanced. We cultivate a modern work environment through an emphasis on wellness, insightful talks and training sessions.
- Striving for Diversity – With colleagues from over 40 nationalities, we recognise the benefits of working with people from all walks of life... check out our Women Transforming Tech highlights reel and our Kedro playlist 🎧
Visit our Careers site to watch our video and read about our interview processes and benefits.
Who You'll Work With
You’ll work with our Marketing & Sales practice in our Singapore office.
As a part of this practice, you’ll focus on developing marketing and sales strategies for leading companies of all major industries, including consumer goods, financial services, retail, chemicals & basic materials, and logistics. Our clients benefit from our experience in core areas of marketing such as branding, customer insights, marketing ROI, digital marketing, CLM pricing, and sales and channel management.
When you join McKinsey as a Data Scientist, you are joining a firm that will challenge you and invest in your professional development. In this role, you will work on the best teams to help the best organizations in the world – in private, public, and social sectors – solve their most difficult problems. You will also work with many experts, from data scientists and researchers to software and app designers.
Our Tech Stack
While we advocate for using the right tech for the right task, we often leverage the following technologies Python, PySpark, TensorFlow, PyTorch, SQL, Airflow, Databricks, our own OSS called Kedro (check out a Kedro tutorial video here), container technologies such as Docker and Kubernetes, cloud solutions such as AWS, GCP or Azure, and more!