Data Scientist II: AI & Analytics Innovator

McKinsey; Toronto; Hybrid; CAD 132,000 - 140,000; Full time

Job summary

McKinsey is seeking a data science professional to collaborate with clients and cross-functional teams to build advanced analytics and AI solutions across industries. You will translate business questions into analytics, conduct data exploration, and deploy models that scale in production.

You will work with senior data scientists and engineers, contribute to R&D, and have opportunities to present at leading conferences.

Qualifications

• Bachelor's/Master's/PhD in a quantitative field and strong ML/data analytics background.
• 2+ years applying ML/data mining to real problems with large datasets.
• Proficiency in SQL and Python; experience with big data tools is a plus.
• Experience deploying ML solutions to production and collaborating with engineers.

Responsibilities

• Translate business questions into analytical approaches and select techniques.
• Conduct exploratory data analysis to uncover insights.
• Design, implement, and evaluate models from traditional ML to DL to LLMs; build RAG pipelines when needed.
• Deploy models via APIs or batch pipelines; write tests and monitor performance and drift.
• Document assumptions, communicate results clearly, and collaborate with engineers to integrate solutions.
• Build models that are accurate, explainable, and bias-free.
• Optimize inference latency and cost with tuning and efficient serving stacks.

Skills

Machine learning

Data mining

Python

SQL

Big data

English fluency

Travel willingness

Education

Master's or PhD in CS/ML/Statistics/Math/Engineering/AI

Tools

PySpark

Hive

Hadoop

Docker

Kubernetes

Databricks

Kedro

Job description

McKinsey is seeking a data science professional to collaborate with clients and cross-functional teams to build advanced analytics and AI solutions across industries. You will translate business questions into analytics, conduct data exploration, and deploy models that scale in production.

You will work with senior data scientists and engineers, contribute to R&D, and have opportunities to present at leading conferences.