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Data Science Phd Jobs in Quebec (NOW HIRING)

Coveo

Senior II Applied Scientist (NLP)

Montreal, QC · On-site

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 ...

Coveo

Senior II Applied Scientist (NLP)

Montreal, QC · On-site

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 ...

Mistral AI

$90 - $130/hr

You hold a PhD / master in AI / data science. * You have 2+ years as a technical individual contributor (data scientist or software engineer) on AI-based products. * You have experience in Fine ...

New

TailorCare

Primary Responsibilities Lead a team of outcome-driven data scientists and ML engineers, with ... Master's or PhD in a quantitative field (computer science, statistics, machine learning, operations ...

CellCarta

Scientist, R&D Proteomics

Montreal, QC · On-site

Monitor data quality and take ownership of project execution in the laboratory * Must be capable of working in a Good Laboratory Practice (GLP) environment Education * M.Sc. or PhD in life sciences ...

PowerToFly

$90 - $120/hr

Attend relevant scientific meetings/conferences and develop summaries of key data presented. Education/Experience Required * PhD, PharmD or MD is required. * Relevant business experience with solid ...

Gilead

Medical Scientist HIV, Quebec

Quebec, QC

D., PhD are preferred) with 5 years of experience in healthcare or pharmaceutical industry ... Through bold and transformative science, we're driving innovation that has the potential to become ...

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Data Science Phd information

What can you do with a doctorate in data science?

A doctorate in data science prepares individuals for advanced roles such as data scientist, research scientist, or machine learning engineer, often involving complex data analysis, modeling, and algorithm development. It enables expertise in programming languages like Python or R, statistical methods, and data management tools, opening opportunities in academia, industry, and research institutions.

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.

Is PhD worth it for data science?

A PhD in data science can enhance expertise in advanced analytics, research, and specialized skills, which may lead to higher-level roles and increased salary potential. However, it also requires significant time and financial investment, and many data science positions value practical experience and skills in programming, machine learning, and data manipulation over formal degrees.

What is the salary of a PhD in data scientist?

A Data Science PhD typically earns between $100,000 and $150,000 annually, depending on experience, industry, and location. Advanced degrees and expertise in machine learning, statistical analysis, and programming tools like Python or R can lead to higher compensation, especially in tech and research sectors.

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.

Is 40 too late for data science?

Data science PhDs can pursue careers at any age, including at 40 or older. Success depends on skills, experience, and continuous learning in areas like programming, statistics, and machine learning, rather than age alone.

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.
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What job categories do people searching Data Science Phd jobs in Quebec look for? The top searched job categories for Data Science Phd jobs in Quebec are:
Data Science Phd jobs near you

Senior II Applied Scientist (NLP)

Coveo

Montreal, QC • On-site

Other

This job post has expired 1 day ago. Applications are no longer accepted.

Job description

Shape the future of enterprise AI technology

Do you want to turn cutting-edge natural language processing into products impacting millions of users?

As a Senior II Applied Scientist on Coveo's Knowledge AI team, you will help build the language technologies at the core of our generative artificial intelligence platform.

You'll take on a technical leadership role, influencing our NLP vision while designing, evaluating, and deploying advanced solutions such as retrieval augmented generation pipelines, information retrieval, semantic search, question answering, and agentic systems, always with real-world constraints in mind.

As one of our Senior II Applied Scientists, you will:
  • Design, develop, and optimize modern language-based artificial intelligence solutions, from data and modeling choices to evaluation strategies and production constraints.
  • Apply and serve transformer-based language models at scale, delivering reliable, real-time experiences to enterprise users.
  • Collaborate closely with machine learning developers and the machine learning platform team to accelerate research and innovation cycles.
  • Act as a technical reference within the team, guiding architectural decisions and promoting best practices in applied science.
  • Mentor applied scientists, supporting their growth and helping raise the overall level of expertise within the group.
  • Contribute to research and development processes that foster efficiency, rigor, and a culture of applied science excellence.
  • Share our innovations externally through technical blog posts, presentations, or other thought leadership content.
Here is what will qualify you for the role:
  • A PhD, or a Master's degree with equivalent research experience, in a relevant field such as machine learning, computer science, mathematics, or physics.
  • At least 8 years of industry experience applying modern natural language processing techniques, including deep learning and large language models, to real-world systems at scale.
  • Strong experience designing models and systems that balance performance, user experience, and production realities.
  • Ability to deliver production-grade code that is well-tested, maintainable, and evaluated through rigorous experimentation.
What will make you stand out:
  • Experience in a technical leadership capacity, including mentoring, hiring, roadmap definition, or scientific project planning.
  • Research or applied experience in areas closely related to Coveo's business, such as information retrieval, neural search, semantic search, or question answering.
  • Exposure to more traditional lexical or linguistics-based natural language processing techniques.
  • International work experience and a demonstrated ability to collaborate across cultures and perspectives.

Do you think you can bring this role to life? Or add your own color?
You don't need to check every single box; passion goes a long way and we appreciate that skillsets are transferable.

Send us your application, we want to hear from you!

Join the Coveolife!

We encourage all qualified candidates to apply regardless of, for example, age, gender, disability, gaps in CV, national or ethnic background.
Coveo is committed to providing accessible employment practices. If you require accommodation due to a disability at any point during the recruitment process, please contact HR@Coveo.com to discuss your needs.

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