Data Scientist II - QuantumBlack, AI by McKinsey (Critical Industries)

Your Impact

As a Data Scientist II, you will collaborate with clients and interdisciplinary teams to understand client needs, develop impactful advanced analytics and AI solutions, optimize code, and solve complex business challenges across industries.

You’ll grow your expertise by contributing to cutting-edge projects, R&D, and global conferences while working alongside top-tier talent in a dynamic, innovative environment.

Your work will drive meaningful change. By uncovering patterns in data and delivering innovative solutions, you’ll help clients stay competitive, transform operations, and achieve lasting improvements. Here’s how you might contribute in a given year:

• Build a digital twin of a defense supply chain to enhance military hardware availability.
• Leverage agentic AI to improve customer service outcomes for a global travel company.
• Optimize the schedule and funding of a multi-billion-dollar capital project to accelerate delivery.

You’ll contribute to projects across industries and data science expertise areas, eventually choosing your own path to build your expertise and skills. You should expect this role to include at least some work in critical industries (Defense, Aerospace, Utilities, Oil and Gas), but you will have the ability to serve other industries as well.

Day to day, you’ll tackle complex challenges in partnership with senior data scientists, engineers, designers, and domain experts. You will:

• Translate business questions into analytical approaches and select the right techniques for each problem
• Conduct exploratory data analysis
• Design, implement, and evaluate models—from traditional machine learning to deep learning to LLMs -- using rigorous metrics and A/B tests. When appropriate, you’ll build production-grade RAG pipelines and assess LLM output quality / hallucinations
• Deploy models via APIs or batch pipelines, write unit tests, and set up monitoring dashboards to track performance and drift
• Document assumptions, communicate results in clear, actionable language, and collaborate with engineers to integrate solutions into user-facing applications.
• Build models which are accurate, explainable, and free from bias
• Optimize inference latency and cost through parameter-efficient tuning, quantization, and accelerated serving stacks
• Additionally, you will contribute to internal tools, participate in R&D projects, and have opportunities to attend and present at leading conferences like NIPS and ICML.

You will be based in one of our U.S. locations and collaborate closely with data scientists, data engineers, machine-learning engineers, designers, and product managers around the world.

Your qualifications and skills

• U.S. Citizenship is required (this role must be able to be staffed on Critical Industries work which includes Defense, Aerospace, Utilities, etc.)
• Bachelor’s degree in computer science with 2+ years of professional experience OR Masters or PhD a discipline such as computer science, mathematics, statistics or electrical engineering
• Professional experience in applying machine learning and data mining techniques to real problems with copious amounts of data
• Development experience (focus on machine learning): SQL and Python’s data-science stack; proficiency with Spark/PySpark for distributed workloads. We use the right tech for the task and often work within clients’ stacks. Technologies you may encounter include Airflow, Databricks, Dask/RAPIDS, containerization with Docker and Kubernetes, and the major clouds (AWS, GCP, Azure, Oracle)
• GenAI experience a plus: parameter-efficient tuning, RAG architectures, vector-store technologies, LLM evaluation
• Exceptional time management to meet your responsibilities in a complex and largely autonomous work environment
• Strong communication skills, both verbal and written, in English and local office language(s), with the ability to adjust your style to suit different perspectives and seniority levels
• Willingness to travel