Data Science Consultant - QuantumBlack, AI by McKinsey

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 colleagues—at all levels—will 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 won’t 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. You’ll make a tangible impact by offering innovative ideas and practical solutions, all while upholding our unwavering commitment to ethics and integrity. 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 firm’s diversity fuels creativity and helps us come up with the best solutions for our clients. Plus, you’ll have the opportunity to learn from exceptional colleagues with diverse backgrounds and experiences. World-class benefits: On top of a competitive salary (based on your location, experience, and skills), we provide a comprehensive benefits package to enable holistic well-being for you and your family. As a data science consultant at QuantumBlack, you will work in multi-disciplinary environments harnessing data to provide real-world impact for organizations globally. You will influence many of the recommendations our clients need to positively change their businesses and enhance performance. In this role, you will be responsible for working on complex and extremely varied data sets from some of the world’s largest organizations to solve real-world problems. You will develop high-quality data science products and solutions for clients as well as assets for our internal data teams, focusing on modeling and working alongside the Data Engineering team. Additionally, you will present findings, recommendations, and provide consultation to stakeholders, both internal and clients. Throughout your tenure, you will learn to work across various industries and sectors, gaining insights into diverse business challenges and applications of data science. You will build large-scale data and analytics solutions, handling complex problems and advanced client situations. You will also learn best practices in data and analytics development, including framework, responsibility model, high-quality code, data security, sustainability, and scalability. Working in collaborative teams with diverse skill sets, you will foster effective teamwork and learn from colleagues in a multicultural and creative environment. Staying up-to-date with the latest advancements in data science tools, techniques, and technologies, as well as participating in first-class learning programs, will be a key part of your development. You will also develop strong client-facing skills, including effective communication, problem-solving, and presentation abilities. You will work with other data scientists, data/ML engineers, designers, project managers, and business subject matter experts on interdisciplinary projects across various industry sectors to enable business ambitions with data and analytics. In terms of who you are, 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 is diverse. While we advocate for using the right tools for the right task, we also take into account the client’s current landscape and preferences. Often, we use Python, PySpark, TensorFlow, PyTorch, Databricks, SQL, Docker, and Kubernetes. We also leverage our own proprietary tools such as Kedro, CausalNex, and MLRun. We work on a regular basis with cloud service providers such as AWS, GCP, and Azure.

Degree in (business) maths, statistics, machine learning, data science, physics, computer science or engineering required Up to 2 years of professional hands-on experience in applying advanced data science methods and implementing technical data solutions (e.g. develop machine learning models), in order to solve business problems A strong grasp of various analytics landscape, including business intelligence, machine learning, AI, and generative AI, and how to apply them effectively in different scenarios Proficiency in Python, SQL (focus on data & analytics applications) Professional experience in cloud-based analytical tools from market-leading providers such as AWS, MS Azure, Google Cloud Effective communication and presentation skills, particularly the ability to explain complex analytical concepts in a comprehensible manner adapted to different groups of non-technical audiences e.g. business managers, heads of products, sales & marketing leads Master degree in data science, computer science, business informatics or equivalent is a plus Practical experience in Generative AI application development Proven record of advisory works Proven record of leadership in a work setting and/or through extracurricular activities Proficient communication skills in German and English