Data Scientist - Marketing & Sales

What you will do:
You will work as part of a fast-paced, cross-functional team building MarketingOS, McKinsey’s AI-powered operating system for modern marketing, and an AI agentics platform that helps clients transform how they plan, activate, measure, and optimize marketing performance.
You will collaborate with data scientists, data engineers, machine learning engineers, product managers, marketing specialists, designers, and business stakeholders to design and build advanced ML, GenAI, and agentic systems that solve complex client challenges across industries.
You will bring deep technical expertise in data modeling, data pipelines, data integrations, data transformations, machine learning, and GenAI application development. You will work with large-scale structured and unstructured datasets across marketing, customer, media, commerce, CRM, and campaign-performance systems.
Also, you will work with leadership and client executives to understand business problems and map them to state-of-the-art analytics and AI solutions. You will solve the hardest business problems with our clients in multiple industries worldwide while leading research and development of state-of-the-art Machine Learning and statistical methods. You will play a leading role in bringing the latest advances in AI and marketing to the clients using data and advanced machine learning models.

Who you will work with:
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.

Your background:
Bachelor’s or Master’s degree in computer science, machine learning, statistics, mathematics, or a related technical field
4+ years of hands-on experience in data science, machine learning, and statistical modeling
Proficiency in Python (pandas, NumPy, scikit-learn), deep learning frameworks (PyTorch, TensorFlow), and big data tools (Spark)
Deep understanding of data models, data pipelines, data transformations, feature engineering, and data quality management
Experience working with large-scale data from multiple systems, including APIs, databases, cloud storage, event streams, and third-party platforms
Expertise building GenAI applications including: Retrieval-Augmented Generation, Agentic workflows, Tool-using agents, Prompt orchestration, Evaluation frameworks, API-based model integrations
Strong understanding of MLOps, CI/CD, model monitoring, QA, risk management, and engineering best practices
Ability to translate ambiguous business problems into analytical, ML, and AI solutions
Collaborative mindset, humility, and strong ownership orientation
Willingness to travel domestically and internationally
Familiarity with marketing and customer data platforms such as Google Ads, Meta Ads, DV360, SA360, Campaign Manager, Adobe, Salesforce, CDPs, CRM systems, data clean rooms, or commerce platforms is preferred
Excellent communication and presentation skills, with the ability to explain complex technical concepts to both technical and non-technical stakeholders