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

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

Do you want to work on complex and pressing challenges—the kind that bring together curious, ambitious, and determined leaders who strive to become better every day? If this sounds like you, you’ve come to the right place.

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, helping clients stay competitive and transform operations.

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.

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, and when appropriate 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 that are accurate, explainable, and free from bias.

Optimize inference latency and cost through parameter‑efficient tuning, quantization, and accelerated serving stacks.

Additionally, 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 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.

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.

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.

Global community :

With colleagues across 65+ countries and over 100 different nationalities, our firm’s diversity fuels creativity and helps us solve the best solutions for our clients.

World‑class benefits :

On top of a competitive salary (based on your location, experience, and skills), we provide a comprehensive benefits package to enable you and your family’s holistic well‑being.

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 Master’s or Ph.D. in a discipline such as computer science, mathematics, statistics, or electrical engineering.

Professional experience 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. 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.

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 applicable law.

Certain U.S. jurisdictions require McKinsey & Company to include a reasonable estimate of the salary for this role. For new joiners for this role in the United States, including all office locations where the job may be performed, a reasonable estimated range is $146,600 - $150,000 USD. This reflects our best estimate of the lowest to highest salary for this role at the time of this posting.

Additionally, we provide a comprehensive benefits package that reflects our commitment to the wellness of our colleagues and their families, including medical, mental health, dental and vision coverage, telemedicine services, life, accident and disability insurance, parental leave and family planning benefits, caregiving resources, a generous retirement contributions program, financial guidance, and paid time off.

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