Senior Data Scientist - QuantumBlack, AI by McKinsey

Role impact

Responsibilities

• Apply deep learning, reinforcement learning, and AI to uncover insights and improve business performance.
• Identify high-potential machine learning initiatives for industry applications and contribute to QuantumBlack’s R&D roadmap.
• Mentor data scientists and lead development and application of advanced machine learning and AI solutions.
• Build end-to-end analytics solutions with multidisciplinary teams to address client challenges and improve operations.

Qualifications and experience

• Master’s or PhD-level degree in computer science, machine learning, applied statistics, mathematics, engineering, artificial intelligence, or a related discipline.
• At least 7 years of deep technical experience in distributed computing, machine learning, and statistics-related work.
• Programming experience in one or more of Python, R, Scala, or SQL.
• Proven commercial application of advanced analytical, data science, and statistical methods.
• Client-facing skills and close teamwork on topics such as data warehousing and machine learning.
• Exceptional time management in a complex, largely autonomous environment; demonstrated thought or people leadership.
• Willingness to travel; strong spoken and written English and local office language(s), with adaptable communication.

Tools and additional knowledge

• The team commonly uses Python, PySpark, the PyData stack, SQL, Airflow, Databricks, Kedro, Dask/RAPIDS, Docker, Kubernetes, AWS, GCP, and Azure; the posting does not require every listed technology.
• Knowledge of distributed computing or NoSQL technologies is a bonus.

Growth and benefits

• The company describes continuous learning, mentorship, coaching, feedback, and opportunities to develop as a leader.
• The role offers collaboration with colleagues across countries and a comprehensive benefits package; salary is described as competitive and dependent on location, experience, and skills.