Data Scientist II - QuantumBlack, AI by McKinsey

QuantumBlack, AI by McKinsey

Toronto

On-site

CAD 120,000 - 190,000

Full time

10 days ago
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Job summary

QuantumBlack, AI by McKinsey is seeking a data-driven ML specialist to collaborate with interdisciplinary teams on advanced analytics and AI solutions across industries. You will translate business questions into analytical approaches, build and evaluate models, and contribute to production deployments.

You will grow through R&D, global conferences, and mentorship while shaping impactful data-driven outcomes for clients in a dynamic, fast-paced environment.

Qualifications

  • Advanced degree in a quantitative field preferred (CS/ML/Statistics).
  • 2+ years applying ML/data mining to real problems with large data.
  • Proficient in Python, SQL and data science stack; experience with big data frameworks is a plus.
  • Experience deploying ML solutions and building production-grade pipelines.

Responsibilities

  • Translate business questions into analytical approaches and select appropriate techniques.
  • Conduct exploratory data analysis and validate models with rigorous metrics and AB tests.
  • Design, implement, and evaluate models from ML to LLMs, including production deployment.
  • Collaborate with engineers to integrate solutions into user-facing applications and dashboards.

Skills

Machine learning
Python
SQL
Data analysis
Big data
English fluency
Experimentation
Deployment

Education

Bachelor's/Master's/PhD in CS/ML/Statistics

Tools

PySpark
Docker
Kubernetes
Databricks

Job description

Who You’ll Work With

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.

Who You’ll Work With

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.

In return for your drive, determination, and curiosity, we’ll provide the resources, mentorship, and opportunities you need to become a stronger leader faster than you ever thought possible. Your colleagues—at all levels—will invest deeply in your development, just as much as they invest in delivering exceptional results for clients. Every day, you’ll receive apprenticeship, coaching, and exposure that will accelerate your growth in ways you won’t find anywhere else.

When you join us, you will have:

  • 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. The real magic happens when you take the input from others to heart and embrace the fast-paced learning experience, owning your journey.
  • 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, all while upholding our unwavering commitment to ethics and integrity. We not only encourage diverse perspectives, but they are critical in driving us toward the best possible outcomes.
  • Global community: With colleagues across 65+ countries and over 100 different nationalities, our firm’s diversity fuels creativity and helps us come up with the best solutions for our clients. Plus, you’ll have the opportunity to learn from exceptional colleagues with diverse backgrounds and experiences.
  • World-class benefits: On top of a competitive salary (based on your location, experience, and skills), we provide a comprehensive benefits package to enable holistic well-being for you and your family.
Your Impact

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 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 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. Here’s how you might contribute in a given year:

  • 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.

You’ll contribute to projects across industries and data science expertise areas, eventually choosing your own path to build your expertise and skills. You should expect your responsibilities to include at least some work in critical industries (Aerospace, Defense, Utilities, Oil and Gas), but you will have the ability to serve other industries as well.

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. When appropriate, you’ll 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

Additionally, you will 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 North America locations and collaborate closely with data scientists, data engineers, machine-learning engineers, designers, and product managers around the world.

Your Qualifications and Skills
  • 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
  • While we advocate for using the right tech for the right task, we often leverage the following technologies: Python, PySpark, the PyData stack, SQL, Airflow, Databricks, our own open-source data pipelining framework called Kedro, Dask/RAPIDS, container technologies such as Docker and Kubernetes, cloud solutions such as AWS, GCP, and Azure, and more
  • Exceptional time management to meet your responsibilities in a complex and largely autonomous work environment.
  • Willingness to travel
  • Strong language fluency skills, both verbal and written, in English, with the ability to adjust your style to suit different perspectives and seniority levels
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