Data Scientist - QuantumBlack, AI by McKinsey

Your Growth

Only at McKinsey

Work on real-world, high-impact projects across a variety of industries - Identify micro patterns in data that our clients can exploit to maintain their competitive advantage and watch your technical solutions transform their day-to-day business.

Experience the best environment to grow as a technologist and a leader - Develop a sought-after perspective connecting technology and business value by working on real-life problems across various industries and technical challenges to serve our clients' changing needs.

Be surrounded by inspiring individuals as part of diverse multidisciplinary teams - Develop a holistic perspective of AI by partnering with the best design, technical, and business talent in the world as your team members.

Our Tech Stack

While we advocate for using the right tech for the right task, we often leverage technologies such as Python, PySpark, the PyData stack, SQL, Airflow, Databricks, Kedro (our open-source data pipelining framework), Dask/RAPIDS, container technologies like Docker and Kubernetes, cloud solutions such as AWS, GCP, and Azure, among others.

Your Impact

As a Data Scientist in the Paris office, you will collaborate with data scientists, data engineers, machine learning engineers, designers, and project managers on interdisciplinary projects, using math, stats, and machine learning to derive structure and knowledge from raw data across various industry sectors.

You will be a highly collaborative individual capable of setting aside your own agenda, listening to and learning from colleagues, challenging thoughtfully, and prioritizing impact.

You will seek ways to improve processes and work collaboratively with colleagues, embracing iterative change, experimenting with new approaches, learning, and improving rapidly.

Role responsibilities:

1. Partner with clients, from data owners and users to C-level executives, to understand their needs and build impactful analytics solutions.
2. Contribute to cross-functional problem-solving sessions with your team and deliver presentations to colleagues and clients.
3. Translate business problems into analytical problems and develop models aimed at solving our clients' and users' problems, ensuring they are evaluated with relevant metrics.
4. Write highly optimized code to advance our internal Data Science Toolbox.
5. Perform Machine Learning & statistical modeling, including implementing Generative AI and LLM use cases.
6. Add real-world impact to your academic expertise, with opportunities to write papers and present at meetings and conferences.
7. Participate in R&D projects, attend conferences such as NIPS and ICML, and engage in data science retrospectives to share and learn from your colleagues; work in one of the most advanced data science teams globally.
8. Work on frameworks and libraries used by data scientists and data engineers to progress from data to impact; guide global companies through data science solutions to transform their businesses across industries including healthcare, automotive, energy, and elite sport.

Your qualifications and skills

• Bachelor's, master's, or PhD in disciplines such as computer science, machine learning, applied statistics, mathematics, engineering, or artificial intelligence.
• 0+ years of professional experience applying machine learning and data mining techniques to real problems with large data sets.
• Programming experience in R and/or Python (must); experience with PySpark/PyData is desirable.
• Ability to prototype statistical analysis and modeling algorithms and apply them to data-driven solutions in new domains.
• Ability to independently own and drive model development, managing demands and deadlines.
• Effective communication skills in English and French, both verbal and written.
• Strong analytical aptitude and good presentation skills, with the ability to explain complex concepts to diverse audiences.
• Willingness to travel.