Data Scientist - QuantumBlack, AI by 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 a variety of industries and technical challenges to serve our clients on their 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 the following technologies Python, PySpark, the PyData stack, SQL, Airflow, Databricks, our own open-source data pipelining framework called Kedro, Dask/RAPIDS, container technologies such as Docker and Kubernetes, cloud solutions such as AWS, GCP, and Azure, and more.

Your Impact
You will work with other 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 who is capable of laying aside your own agenda, listening to and learning from colleagues, challenging thoughtfully and prioritizing impact. You search for ways to improve things and work collaboratively with colleagues. You believe in iterative change, experimenting with new approaches, learning and improving to move forward quickly.

As a Data Scientist, you’ll

• Partner with our clients, from data owners and users to C-level executives, to understand their needs and build impactful analytics solutions.
• Contribute to cross-functional problem-solving sessions with your team and deliver presentations to colleagues and client.
• Translate business problems into analytical problems and develop models aimed at solving our clients and users problems and ensure they are evaluated with the relevant metrics.
• Write highly optimized code to advance our internal Data Science Toolbox.
• You will do Machine Learning & statistical modelling as well as implementing Generative AI and LLM use cases.
• Add real-world impact to your academic expertise, as you are encouraged to write papers and present at meetings and conferences should you wish.
• You will take part in R&D projects; attend conferences such as NIPS and ICML as well as data science retrospectives where you will have the opportunity to share and learn from your co-workers; work in one of the most advanced data science teams globally.
• Work on the frameworks and libraries that our teams of data scientists and data engineers use to progress from data to impact; 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.

Your Qualifications and Skills

• Bachelor's, master's or PhD level in a discipline such as computer science, machine learning, applied statistics, mathematics, engineering or artificial intelligence
• 0-2 years of professional experience in applying machine learning and data mining techniques to real problems with copious amounts of data
• Programming experience (focus on machine learning) R and/or Python (must). Experience with PySpark/PyData is desirable
• Ability to prototype statistical analysis and modeling algorithms and apply these algorithms for data driven solutions to problems in new domains
• Ability to independently own and drive model development, balancing demands and deadlines
• Demonstrated aptitude for analytics
• Good presentation and communication skills, with the ability to explain complex analytical concepts to people from other fields
• Willingness to travel