Job Details

Overview

Digital Data Scientist II - QuantumBlack, AI by McKinsey (Critical Industries) | Job ID: 100741

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 are some example contributions 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 will 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 Growth

Driving lasting impact and building long-term capabilities with our clients is challenging work. You are the kind of person who thrives in a high-performance/high-reward culture—doing hard things, recovering from setbacks, and trying new approaches.

In return for your drive, determination, and curiosity, we provide the resources, mentorship, and opportunities you need to become a stronger leader faster than you might expect. Your colleagues—at all levels—will invest in your development as much as in delivering exceptional results for clients. Every day, you'll receive apprenticeship, coaching, and exposure that will accelerate your growth.

When you join us, you will have:

• Continuous learning: Our learning and apprenticeship culture, backed by structured programs, helps you grow while creating an environment where feedback is clear, actionable, and focused on your development.
• 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, with diverse perspectives encouraged to drive the best outcomes.
• Global community: With colleagues across 65+ countries and over 100 nationalities, our firm's diversity fuels creativity and better solutions for clients.
• World-class benefits: In addition to a competitive salary, a comprehensive benefits package supports well-being for you and your family.

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 in computer science, mathematics, statistics or electrical engineering
• Professional experience applying machine learning and data mining techniques to real problems with large data sets
• Development experience (machine learning focus): SQL and Python data-science stack; proficiency with Spark/PySpark for distributed workloads. Technologies you may encounter include Airflow, Databricks, Dask/RAPIDS, Docker, Kubernetes, and 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 responsibilities in a complex, autonomous environment
• Strong communication skills in English (and local office language(s) where applicable), with ability to adapt style to various audiences
• Willingness to travel

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 law. Certain US jurisdictions require salary information; the posted range is provided for new joiners in the United States: $146,600 - $150,000 USD, with final offer dependent on location, experience, and business needs. Additional benefits include medical, dental, vision, life, disability insurance, parental leave, retirement contributions, financial guidance, and paid time off. For non-U.S. applicants, McKinsey & Company is an Equal Opportunity employer. For details on our global EEO policy and diversity initiatives, please visit the McKinsey Careers and Diversity & Inclusion sites.