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

McKinsey-posted 2 months ago
Mid Level
San Francisco, CA
5,001-10,000 employees
Professional, Scientific, and Technical Services
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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.

  • 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
  • Build production-grade RAG pipelines and assess LLM output quality / hallucinations when appropriate
  • 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
  • Contribute to internal tools, participate in R&D projects, and have opportunities to attend and present at leading conferences like NIPS and ICML
  • U.S. Citizenship is required
  • Bachelor's degree in computer science with 2+ years of professional experience OR Masters or PhD in 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
  • GenAI experience a plus: parameter-efficient tuning, RAG architectures, vector-store technologies, LLM evaluation
  • Exceptional time management to meet 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 style to suit different perspectives and seniority levels
  • Willingness to travel
  • Competitive salary based on location, experience, and skills
  • Comprehensive benefits package to enable holistic well-being for you and your family
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