Data Scientist - QuantumBlack, AI by McKinsey
McKinsey & Company
Software Engineering, Data Science
Melbourne, VIC, Australia · Perth, WA, Australia · Sydney, NSW, Australia
Posted on Apr 2, 2025
Data Scientist - QuantumBlack, AI by McKinsey
Job ID: 96591
Do you want to work on complex and pressing challenges—the kind that bring together curious, ambitious, and determined leaders who strive to become better every day? If this sounds like you, you’ve come to the right place.
Your Impact
Only at McKinsey, you will 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.
You will 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. You will 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.
As a Data Scientist, you will:
- 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.
- Add real-world impact to your academic expertise, as you are encouraged to write papers and present at meetings and conferences should you wish.
- 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.
- Guide global companies through data science solutions to transform their businesses and enhance performance across industries including healthcare, automotive, energy and elite sport.
Your Growth
You will be part of our global Data Science community and 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 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.
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 qualifications and skills
- Bachelors, Masters or PhD level in a discipline such as: computer science, machine learning, applied statistics, mathematics, engineering or artificial intelligence
- 2-5 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): SQL and Python’s Data Science stack are a must; good knowledge of at least one big data framework (Pyspark, Hive, Hadoop) is a plus; R, SPSS, SAS (nice to have); Software Engineering is a plus
- Ability to prototype statistical analysis and modeling algorithms and apply these algorithms for data driven solutions to problems in new domains
- Experience deploying technology applied to business problems is a plus
- Knowledge in applying machine learning solution to real problems with complex and/or big amounts of data.
- Willingness to travel
Please review the additional requirements regarding essential job functions of McKinsey colleagues.
FOR U.S. APPLICANTS: McKinsey & Company is an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by applicable law.
FOR NON-U.S. APPLICANTS: McKinsey & Company is an Equal Opportunity employer. For additional details regarding our global EEO policy and diversity initiatives, please visit our McKinsey Careers and Diversity & Inclusion sites.
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Job Skill Group - N/A
Job Skill Code - SADS - Data Scientist II
Function - Technology
Industry - High Tech
Post to LinkedIn - Yes
Posted to LinkedIn Date - Fri Mar 28 00:00:00 GMT 2025
LinkedIn Posting City - Sydney
LinkedIn Posting State/Province -
LinkedIn Posting Country - Australia
LinkedIn Job Title - Data Scientist - QuantumBlack, AI by McKinsey
LinkedIn Function - Consulting;Information Technology
LinkedIn Industry - Computer Software;Information Technology and Services;Internet
LinkedIn Seniority Level - Executive
Job Skill Code - SADS - Data Scientist II
Function - Technology
Industry - High Tech
Post to LinkedIn - Yes
Posted to LinkedIn Date - Fri Mar 28 00:00:00 GMT 2025
LinkedIn Posting City - Sydney
LinkedIn Posting State/Province -
LinkedIn Posting Country - Australia
LinkedIn Job Title - Data Scientist - QuantumBlack, AI by McKinsey
LinkedIn Function - Consulting;Information Technology
LinkedIn Industry - Computer Software;Information Technology and Services;Internet
LinkedIn Seniority Level - Executive