Data Scientist II - QuantumBlack, AI by McKinsey

About the role

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.

Responsibilities

• 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, 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
• Contribute to internal tools, participate in R&D projects, and have opportunities to attend and present at leading conferences like NIPS and ICML

Requirements

• Bachelors, Masters or PhD level in a discipline such as: computer science, machine learning, applied statistics, mathematics, engineering or artificial intelligence
• 2+ years of professional experience in applying machine learning and data mining techniques to real problems with copious amounts of data
• Programming experience (focus on machine learning): SQL and Python’s Data Science stack are a must; good knowledge of at least one big data framework (Pyspark, Hive, Hadoop) is a plus; R, SPSS, SAS (nice to have); Software Engineering is a plus
• Knowledge in applying machine learning solutions to real problems with complex and/or big amounts of data
• Ability to prototype statistical analysis and modeling algorithms and apply these algorithms for data driven solutions to problems in new domains
• Experience deploying technology applied to business problems is a plus
• Exceptional time management to meet your responsibilities in a complex and largely autonomous work environment
• Willingness to travel

Qualifications

• Strong language fluency skills, both verbal and written, in English, with the ability to adjust your style to suit different perspectives and seniority levels