Data Scientist I

About the Role

As a Data Scientist I within QuantumBlack, AI by McKinsey, you will join a dynamic, global team that is passionate about leveraging analytics and artificial intelligence to deliver business impact for a broad roster of clients. Located in London, you will work alongside colleagues from various backgrounds—including data scientists, engineers, designers, and product managers—on projects across industries such as healthcare, automotive, energy, and sports. The work environment values resilience, curiosity, and determination, fostering rapid professional growth through mentorship and structured learning. Your contributions will directly affect client operations and performance, while allowing you to develop both technically and as a leader.

Key Responsibilities

• Partner with clients to translate business requirements into complex analytical problems, designing and deploying solutions that deliver measurable value.
• Develop, prototype, and implement models using advanced statistical and machine learning techniques on large datasets.
• Work collaboratively with interdisciplinary teams to optimize codebases and analytical workflows.
• Contribute to the creation and enhancement of internal tools and frameworks such as Kedro and Databricks.
• Participate in research and development projects, with opportunities to attend and present at industry-leading conferences.
• Clearly communicate methodologies and findings to both technical and non-technical stakeholders.
• Maintain high standards of ethics, integrity, and transparency in project work.
• Manage time effectively while handling multiple concurrent priorities in a fast-paced, largely autonomous setting.
• Be open to occasional travel as required by client projects.

Qualifications

• Possess a Bachelor’s, Master’s, or PhD in a technical field such as Computer Science, Machine Learning, Mathematics, Applied Statistics, Engineering, or Physics.
• Have up to 2 years of relevant industry experience utilizing machine learning and data mining on significant datasets.
• Demonstrated experience with programming languages and tools focused on analytics and machine learning, especially Python and/or R. Knowledge of SPSS, SAS, or similar tools is advantageous.
• Familiarity with modular data science stacks, including PySpark, SQL, Airflow, Databricks, and Docker; cloud platforms like AWS, GCP, or Azure are plus points.
• Experience or exposure to Generative AI (GenAI) and agentic systems provides a competitive advantage.
• Strong analytical aptitude and genuine enthusiasm for resolving complex data challenges.
• Excellent communication skills in English, capable of adapting explanations for various audiences.
• Effective time management and organizational capabilities to operate independently within complex project environments.

Professional Development & Culture

• Engage in continuous learning through structured programs and active mentorship.
• Contribute immediately, with your ideas respected and given real impact.
• Join a diverse community that champions creativity and holistic problem-solving across more than 65 countries.

Compensation & Benefits

• Competitive salary tailored to your experience, skills, and location.
• A comprehensive benefits suite that emphasizes your holistic well-being and that of your family.