Data Scientist - QuantumBlack

QuantumBlack, AI by McKinsey; Singapore; On-site; USD 80,000 - 130,000; Full time

Job summary

Join a forward-thinking company where you will collaborate with diverse teams to solve real-world problems using advanced machine learning techniques. As a Data Scientist, you will leverage your expertise in Python, SQL, and various data frameworks to develop innovative solutions that drive business impact across multiple industries. You'll engage in high-impact projects, contribute to research and development, and be part of a culture that values continuous learning and improvement. This role offers a unique opportunity to grow as a technologist while making a significant difference in the field of AI.

Qualifications

• 2+ years of experience in machine learning and data mining with large datasets.
• Proficiency in SQL and Python's Data Science stack.

Responsibilities

• Partner with clients to understand needs and build impactful analytics solutions.
• Translate business problems into analytical problems and develop models.

Skills

Machine Learning

Data Mining

Python

SQL

PySpark

Statistical Analysis

Data Visualization

Education

Bachelor's in Computer Science

Master's in Machine Learning

PhD in Applied Statistics

Tools

Docker

Kubernetes

AWS

GCP

Azure

Databricks

Airflow

Job description

Who You'll Work With

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 are a highly collaborative individual capable of setting aside your own agenda, listening to and learning from colleagues, challenging thoughtfully, and prioritizing impact. You seek ways to improve processes and work collaboratively. You believe in iterative change, experimenting with new approaches, learning, and improving to move forward quickly.

Your Impact

Only at McKinsey will you work on real-world, high-impact projects across various industries. You will have the opportunity to collaborate with QB/Labs teams and build complex, innovative ML systems to accelerate AI work and solve business problems at speed and scale.

This environment fosters growth as a technologist and leader. You will develop a perspective connecting technology and business value by working on real-life problems across industries and technical challenges to serve our clients' evolving needs.

You will be part of diverse, multidisciplinary teams, developing a holistic AI perspective by partnering with top design, technical, and business talent worldwide.

While we advocate for using the right tech for the right task, our technologies often include Python, PySpark, the PyData stack, SQL, Airflow, Databricks, Kedro, Dask/RAPIDS, Docker, Kubernetes, and cloud solutions like AWS, GCP, and Azure.

As a Data Scientist, you will

• Partner with 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 and deliver presentations to colleagues and clients.
• Translate business problems into analytical problems and develop models aimed at solving these issues, ensuring they are evaluated with relevant metrics.
• Write optimized code to advance our internal Data Science Toolbox.
• Contribute to research and development, including publishing papers and presenting at conferences like NIPS and ICML, if desired.
• Participate in R&D projects and data science retrospectives to share knowledge and learn from colleagues.
• Work within one of the most advanced data science teams globally.
• Develop frameworks and libraries used by data scientists and engineers to turn data into impact.
• Guide global companies in data science solutions to transform their businesses across industries such as healthcare, automotive, energy, and sports.

Your Qualifications and Skills

• Bachelor's, master's, or PhD in computer science, machine learning, applied statistics, mathematics, engineering, or AI.
• At least 2 years of professional experience applying machine learning and data mining techniques to real problems with large datasets.
• Proficiency in programming, especially in SQL and Python's Data Science stack; knowledge of big data frameworks like PySpark, Hive, Hadoop is a plus; familiarity with R, SPSS, SAS is nice to have; software engineering skills are advantageous.
• Ability to prototype statistical analyses and models, applying these algorithms to data-driven solutions in new domains.
• Experience deploying technology solutions to business problems is a plus.
• Knowledge of applying machine learning solutions to complex, large-scale data problems.
• Understanding of prompt engineering and GenAI applications (RAG, Agentic systems), with a basic grasp of engineering standards, QA, and risk management.
• Willingness to travel.