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Job Title


Data Scientist - QuantumBlack, AI by McKinsey


Company : McKinsey & Company, Inc.


Location : Perth, Australia


Created : 2026-02-02


Job Type : Full Time


Job Description

Your Growth Driving lasting impact and building long-term capabilities with our clients is not easy work. You are the kind of person who thrives in a high performance/high reward culture - doing hard things, picking yourself up when you stumble, and having the resilience to try another way forward. In return for your drive, determination, and curiosity, we''ll provide the resources, mentorship, and opportunities you need to become a stronger leader faster than you ever thought possible. Your colleaguesat all levelswill invest deeply in your development, just as much as they invest in delivering exceptional results for clients. Every day, you''ll receive apprenticeship, coaching, and exposure that will accelerate your growth in ways you wont find anywhere else. When you join us, you will have: Continuous learning: Our learning and apprenticeship culture, backed by structured programs, is all about helping you grow while creating an environment where feedback is clear, actionable, and focused on your development. The real magic happens when you take the input from others to heart and embrace the fast-paced learning experience, owning your journey. A voice that matters: From day one, we value your ideas and contributions. Youll make a tangible impact by offering innovative ideas and practical solutions. We not only encourage diverse perspectives, but they are critical in driving us toward the best possible outcomes. Global community: With colleagues across 65+ countries and over 100 different nationalities, our firms diversity fuels creativity and helps us come up with the best solutions for our clients. Plus, youll have the opportunity to learn from exceptional colleagues with diverse backgrounds and experiences. Worldclass benefits: On top of a competitive salary (based on your location, experience, and skills), we provide a comprehensive benefits package to enable holistic wellbeing for you and your family. Your Impact You will work on realworld, highimpact projects across a variety of industries, identify micropatterns in data that our clients can exploit to maintain their competitive advantage and watch your technical solutions transform their daytoday business. You will experience the best environment to grow as a technologist and a leader, develop a soughtafter perspective connecting technology and business value by working on reallife 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 Clevel executives, to understand their needs and build impactful analytics solutions. Contribute to crossfunctional problemsolving sessions with your team and deliver presentations to colleagues and clients. 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 realworld 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 coworkers. 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. 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 can lay 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 opensource 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 disciplines 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 Pythons 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 solutions to real problems with complex and/or big amounts of data. Willingness to travel. #J-18808-Ljbffr