Data Scientist II

About the Role

Join QuantumBlack, AI by McKinsey in Singapore as a Data Scientist II, where you will tackle challenging, impactful problems across various industries by developing advanced machine learning systems. Thrive in our high-performance culture by embracing resilience, curiosity, and continuous learning. Experience dedicated mentorship and coaching, coupled with access to global expert communities and world-class benefits designed to support your holistic well-being.

Your Impact

• Collaborate closely with clients—and within multidisciplinary teams—to understand business goals and design analytics solutions that drive measurable impact.
• Engage deeply in translating complex business challenges into analytical models that address client and user needs, ensuring accuracy with relevant performance metrics.
• Develop and maintain efficient, high-quality code to enhance our internal Data Science Toolbox.
• Contribute academically and professionally by authoring publications and representing the company at conferences such as NIPS and ICML.
• Participate actively in R&D efforts and data science retrospectives to foster continuous innovation and knowledge sharing.
• Influence transformative business outcomes for global clients in sectors including healthcare, automotive, energy, and elite sports by providing data-driven solutions.

Working Environment

You will be part of one of the world's most advanced data science teams, collaborating with experts in data science, engineering, machine learning, design, and project management. Our international community spans over 65 countries and 100 nationalities, enriching creativity and innovation.

Qualifications and Skills

• Degree (Bachelor’s, Master’s, or PhD) in computer science, machine learning, applied statistics, mathematics, engineering, or artificial intelligence.
• At least 2 years professional experience applying machine learning and data mining techniques to complex, large datasets.
• Proficiency in programming for machine learning, including SQL and Python’s data science libraries; familiarity with big data frameworks like PySpark, Hive, or Hadoop is advantageous.
• Experience prototyping statistical models and applying them to novel problems across domains.
• Exposure to deploying technological solutions to business challenges is beneficial.
• Knowledge of modern machine learning approaches, including prompt engineering and generative AI applications such as retrieval-augmented generation (RAG) and agentic systems.
• Awareness of engineering standards, quality assurance, and risk management in AI development.
• Willingness to travel as required for client engagement and collaboration.

Additional Information

Our culture emphasizes ownership over your professional growth, offering clear, actionable feedback in a fast-paced environment. Diverse perspectives are deeply valued and essential for achieving the best outcomes. A competitive salary and comprehensive benefits package reflective of your experience and location are provided to support you and your family.