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Data Science Phd Jobs in Quebec (NOW HIRING)

A Masters or PHD in a quantitative field (i.e. Physics, Computer Science, Stats) * 1-2 years ... Confident extracting and manipulating data from SQL and noSQL stores * Previous experience with ...

Data Scientist

Montreal, QC · On-site

$80K - $100K/yr

A Masters or PHD in a quantitative field (i.e. Physics, Computer Science, Stats) * 1-2 years ... Confident extracting and manipulating data from SQL and noSQL stores * Previous experience with ...

Our state-of-the-art data technologies, lean AI agile methodologies, and cohesive teams of elite ... Advanced degree (MSc or PhD) in a quantitative field - statistics, mathematics, computer science ...

MSc and/or PhD are an asset. * Minimum of 2 years of experience in data science, machine learning and advanced statistics solving business problems. * Technical Skills: Proficiency in multiple ...

MSc and/or PhD are an asset. * Minimum of 2 years of experience in data science, machine learning and advanced statistics solving business problems. * Technical Skills: Proficiency in multiple ...

Proficient with python data-science libraries ( pandas, numpy, bokeh ) * Expertise in combinatorial and graph optimization algorithms * A Masters or PHD in Computer Science, Engineering. or ...

Proficient with python data-science libraries ( pandas, numpy, bokeh ) * Expertise in combinatorial and graph optimization algorithms * A Masters or PHD in Computer Science, Engineering. or ...

Proficient with python data-science libraries ( pandas, numpy, bokeh ) * Expertise in combinatorial and graph optimization algorithms * A Masters or PHD in Computer Science, Engineering. or ...

Proficient with python data-science libraries ( pandas, numpy, bokeh ) * Expertise in combinatorial and graph optimization algorithms * A Masters or PHD in Computer Science, Engineering. or ...

A PhD, or a Master's degree with equivalent research experience, in a relevant field such as ... computer science, mathematics, or physics. * At least 8 years of industry experience applying ...

A PhD, or a Master's degree with equivalent research experience, in a relevant field such as ... computer science, mathematics, or physics. * At least 8 years of industry experience applying ...

A PhD, or a Master's degree with equivalent research experience, in a relevant field such as ... computer science, mathematics, or physics. * At least 8 years of industry experience applying ...

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Data Science Phd information

What are the key skills and qualifications needed to thrive as a Data Science PhD, and why are they important?

To thrive as a Data Science PhD, you need advanced expertise in statistics, machine learning, data analysis, and a doctoral degree in a quantitative field. Proficiency in programming languages like Python or R, experience with big data frameworks (e.g., Spark, Hadoop), and familiarity with data visualization tools are typically required. Critical thinking, problem-solving, and strong communication skills help you translate complex data insights for diverse stakeholders. These skills are vital for driving innovative research, making data-driven decisions, and contributing impactful solutions in data-centric environments.

What jobs can you get with a PhD in data science?

A PhD in data science qualifies individuals for advanced roles such as data scientist, machine learning engineer, research scientist, and data science consultant. These positions often require strong programming skills in Python or R, experience with big data tools, and the ability to develop complex models and algorithms. Graduates may work in industries like technology, finance, healthcare, or academia, often in research or leadership capacities.

What is the salary of a PhD in data science?

A PhD in data science typically earns between $100,000 and $150,000 annually in the United States, depending on experience, industry, and location. Senior roles or positions in high-demand sectors can offer higher compensation, often exceeding $160,000. Advanced skills in machine learning, statistical analysis, and programming are highly valued in this field.

What is the 80 20 rule in data science?

In data science, the 80/20 rule, also known as the Pareto principle, suggests that roughly 80% of results come from 20% of the efforts or features. Data scientists often use this concept to focus on the most impactful variables or tasks to optimize model performance and efficiency.

What are some common challenges faced by Data Science PhDs when transitioning from academia to industry roles?

Data Science PhDs often encounter challenges such as adapting to the faster pace and collaborative nature of industry projects compared to academic research. In industry, there is a greater emphasis on delivering practical solutions within tight deadlines and working closely with cross-functional teams like engineering and product management. Additionally, data science work in industry may require balancing technical rigor with business impact, often prioritizing actionable insights over exhaustive analysis. Building strong communication and stakeholder management skills can help ease this transition.

What is a Data Science PhD?

A Data Science PhD is a doctoral-level degree focused on advanced research in data science, which combines elements of statistics, computer science, and domain expertise. Students in a Data Science PhD program typically work on developing new methods for analyzing large datasets, creating machine learning algorithms, and addressing complex problems in areas such as artificial intelligence, data mining, and predictive analytics. Graduates are prepared for careers in academia, research, and industry, where they can lead data-driven projects and contribute to advancements in the field.

Is doing a PhD in data science worth it?

A PhD in data science can lead to advanced roles in research, academia, or specialized industry positions requiring deep expertise in machine learning, statistical analysis, and programming. It typically involves several years of study and research, which can increase earning potential and job opportunities but also requires significant time and effort investment. The decision depends on career goals and whether advanced research or teaching roles align with your interests.
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Infographic showing various Data Science Phd job openings in Quebec as of June 2026, with employment types broken down into 97% Full Time, 2% Part Time, and 1% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution.
Expert, AI & Data Science

Other

Posted yesterday


Canadian National Railway rating

7.3

Company rating: 7.3 out of 10

Based on 48 frontline employees who took The Breakroom Quiz

158th of 341 rated logistics


Job description

Expert, AI & Data Science

At CN, everyday brings new and exciting challenges. You can expect an interesting environment where you're part of making sure our business is running optimally and safely-helping keep the economy on track. We provide the kind of paid training and opportunities that long-term careers are built on and we recognize hard workers who strive to make a difference. You will be able to thrive in our close-knit, safety-focused culture working together as ONE TEAM. The careers we offer are meaningful because the work we do matters. Join us! 
Job Summary

You will be part of a team that spans across all business domains.  You will provide advanced analytical insights using data analysis and machine learning techniques.   You will collaborate with teams across the company, exploring various data sources to help identify new opportunities while driving the adoption of AI.   As an expert data scientist, you will combine your knowledge of machine learning and software development skills to automate model development, training, and deployment.  You will leverage your experience in building reusable algorithms, functions, and libraries to use in model development for predictive and prescriptive analytics.   

Main Responsibilities

  • Work with structured and unstructured raw data to design and develop innovative predictive models, metrics, and dashboards to uncover actionable insights
  • Visualize and report data findings creatively in a variety of visual formats that provide insights to the organization
  • Influence how we approach business challenges and opportunities by driving the adoption of a data driven mindset
  • Support and evolve the Advanced Analytics and Data Science roadmap by leveraging industry research, best practices, and emerging tools/technology
  • Collaborate on end-to-end automation efforts required to bring models to production
  • Build and maintain a strong engagement with key stakeholders to understand business needs and priorities

Requirements

  • Experience in the application of data mining and analysis, predictive modeling, statistics, and other advanced analytical techniques with hands-on work experience
  • 7-8 or more years of hands-on work and practical business experience in Machine Learning and AI, including classification, clustering, time series analysis, NLP, demand forecasting and optimization
  • Excellent communication skills and capable of breaking down technical and complex concepts in a way that is understood by non-technical audiences

Education/Certification/Designation

  • Masters or PhD degree in a quantitative field such as Math, Statistics, Computer Science, Economics, or Data Science

Technical Skills/Knowledge

  • Solid development experience with Python and comfortable using various data science libraries such as Scikit-learn, Pandas, NumPy as well as frameworks like TensorFlow, Pytorch, Keras and have applied these skills towards solving actual business matters
  • Comfortable working in and with a Jupyter like environment and infrastructure, and familiar with GitHub, Data bricks
  • Have advanced knowledge in SQL and Apache Spark, Google VertexAI, Gemini, Microsoft Copilot, Databricks, Generative AI
  • Expert level experience with at least one of the cloud computing platforms - Azure, AWS, GCP
  • Familiar with Tableau and/or Power BI visual analytics purposes
  • Well versed in software and AI development lifecycles, including ML Ops
  • Have agile experience and have a bias for action, removing blocks to get results fast
  • Fluently bilingual both written and verbal (English, French)* 
    *Any knowledge for any of the above would be considered as an asset 

Assets

  • Experience with SAFe agile methodology and work in a fast-paced environment
  • Having Azure or other cloud certifications, For example Azure Data Lake, Data Bricks

About CN  
CN is a world-class transportation leader and trade-enabler. Essential to the economy, to the customers, and to the communities it serves, CN safely transports more than 300 million tons of natural resources, manufactured products, and finished goods throughout North America every year. As the only railroad connecting Canada's Eastern and Western coasts with the Southern tip of the U.S. through a 19,500 mile rail network, CN and its affiliates have been contributing to community prosperity and sustainable trade since 1919. CN is committed to programs supporting social responsibility and environmental stewardship. At CN, we work as ONE TEAM, focused on safety, sustainability and our customers, providing operational and supply chain excellence to deliver results. 


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