QuantumBlack, AI by McKinsey
Data Scientist II QuantumBlack, AI by McKinsey
QuantumBlack, AI by McKinsey, Chicago, Illinois, United States, 60290
Data Scientist II QuantumBlack, AI by McKinsey
Data Scientist II QuantumBlack, AI by McKinsey
role at QuantumBlack, AI by McKinsey. Overview
As a Data Scientist II, you will collaborate with clients and interdisciplinary teams to understand needs, develop impactful advanced analytics and AI solutions, optimize code, and solve complex business challenges across industries. You will 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 Responsibilities
Translate business questions into analytical approaches and select the right techniques for each problem. Conduct exploratory data analysis to inform modeling and business decisions. Design, implement, and evaluate modelsfrom traditional machine learning to deep learning to LLMsusing rigorous metrics and A/B tests; where appropriate, build production?grade RAG pipelines and assess LLM output quality and 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 clearly, 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. Contribute to internal tools, participate in R&D projects, and have opportunities to attend and present at leading conferences like NIPS and ICML. Be based in one of the U.S. locations and collaborate with data scientists, data engineers, ML engineers, designers, and product managers around the world. Your Qualifications and Skills
Bachelors 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 with focus on machine learning: SQL and Pythons data-science stack; proficiency with Spark/PySpark for distributed workloads; experience with Airflow, Databricks, Dask/RAPIDS, Docker and Kubernetes; and major clouds (AWS, GCP, Azure, Oracle). GenAI experience a plus: parameter-efficient tuning, RAG architectures, vector-store technologies, and LLM evaluation. Exceptional time management to meet responsibilities in a complex and largely autonomous environment. Strong communication skills, both verbal and written, in English and local office language(s), with the ability to adjust style to different perspectives and seniority levels. Willingness to travel. Job Details
Seniority level: Data Scientist II Employment type: Full-time Job function: Consulting and Information Technology Industries: Software Development and IT Services and IT Consulting
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Data Scientist II QuantumBlack, AI by McKinsey
role at QuantumBlack, AI by McKinsey. Overview
As a Data Scientist II, you will collaborate with clients and interdisciplinary teams to understand needs, develop impactful advanced analytics and AI solutions, optimize code, and solve complex business challenges across industries. You will 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 Responsibilities
Translate business questions into analytical approaches and select the right techniques for each problem. Conduct exploratory data analysis to inform modeling and business decisions. Design, implement, and evaluate modelsfrom traditional machine learning to deep learning to LLMsusing rigorous metrics and A/B tests; where appropriate, build production?grade RAG pipelines and assess LLM output quality and 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 clearly, 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. Contribute to internal tools, participate in R&D projects, and have opportunities to attend and present at leading conferences like NIPS and ICML. Be based in one of the U.S. locations and collaborate with data scientists, data engineers, ML engineers, designers, and product managers around the world. Your Qualifications and Skills
Bachelors 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 with focus on machine learning: SQL and Pythons data-science stack; proficiency with Spark/PySpark for distributed workloads; experience with Airflow, Databricks, Dask/RAPIDS, Docker and Kubernetes; and major clouds (AWS, GCP, Azure, Oracle). GenAI experience a plus: parameter-efficient tuning, RAG architectures, vector-store technologies, and LLM evaluation. Exceptional time management to meet responsibilities in a complex and largely autonomous environment. Strong communication skills, both verbal and written, in English and local office language(s), with the ability to adjust style to different perspectives and seniority levels. Willingness to travel. Job Details
Seniority level: Data Scientist II Employment type: Full-time Job function: Consulting and Information Technology Industries: Software Development and IT Services and IT Consulting
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