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Data Cleaning Jobs in Quebec (NOW HIRING)

... Data Center, and Pharma/Healthcare Industry. Our Technical Site Services group specializes in ... We are seeking an experienced Cleaning Technician to join our team. Job Summary: The ideal ...

Data Analyst

Montreal, QC · On-site +1

CA$64K - CA$69K/yr

Data Analyst Location: Anywhere in Canada (Hybrid and Remote) Reports to: Head of Insights and ... clean alternatives, carrying out peaceful acts of civil disobedience and engaging the public. To ...

Data Analyst

Montreal, QC · On-site

CA$64K - CA$69K/yr

Data Analyst Location: Anywhere in Canada (Hybrid and Remote) Reports to: Head of Insights and ... clean alternatives, carrying out peaceful acts of civil disobedience and engaging the public. To ...

Data Engineer

Montreal, QC · On-site +1

CA$80 - CA$85/hr

... clean and maintainable code in a CI-CD Environment Experience in using cloud BI technologies such as Azure or similar Experience in translating business requirements into advanced data models able to ...

Clean, transform, structure, and analyze large volumes of data from multiple systems (100,000+ SKUs) * Act as a subject matter expert for Master Data Clerks and contribute to the evolution of best ...

At ABB, we help industries run leaner and cleaner-and every person here makes that happen. You'll ... Marketing Manager As a Product Data Analyst (6 months contract), you will lead the management of ...

You will centralize fragmented studio data, including project roadmaps, telemetry, feature backlogs, and release timelines, to create clean, structured data layers that provide critical visibility ...

Help design automated pipelines (Airflow) for data ingestion and cleaning. * Production Engineering: Optimize models for low-latency inference (quantization, distillation, TensorRT/ONNX) and support ...

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Data Cleaning information

What is a data cleaning?

A Data Cleaning job involves identifying and correcting errors, inconsistencies, and inaccuracies in datasets to ensure high-quality data for analysis. This process includes removing duplicate records, filling in missing values, standardizing formats, and eliminating irrelevant or erroneous data. Data cleaning helps improve data accuracy, reliability, and usability for business intelligence, machine learning, and decision-making. Professionals in this role typically work with databases, spreadsheets, and data management tools to refine raw data into a structured and meaningful format.

What are the key skills and qualifications needed to thrive in data cleaning, and why are they important?

To thrive in Data Cleaning, you need a strong attention to detail, analytical skills, and a solid understanding of data management practices, often supported by training or coursework in data science, statistics, or information technology. Familiarity with tools like Microsoft Excel, SQL, Python (with libraries such as pandas), or specialized data cleaning software is highly valuable. Excellent problem-solving abilities, persistence, and effective communication are important soft skills for identifying and addressing data inconsistencies while collaborating with other team members. These skills are essential to ensure that datasets are accurate, reliable, and ready for analysis, leading to trustworthy business insights.

What are the most common challenges faced by professionals in data cleaning roles?

One of the biggest challenges in data cleaning is dealing with incomplete, inconsistent, or duplicate data from multiple sources, which often requires creative problem-solving and close attention to detail. Communicating with team members to clarify data definitions and intended use is also a frequent part of the job, as misinterpretations can lead to errors. Additionally, deadlines and large datasets can make the role fast-paced, so strong organizational skills and efficiency are important. However, overcoming these challenges offers valuable experience and plays a crucial role in ensuring the success of projects that depend on high-quality data.

What skills are needed for data cleaning?

Data cleaning requires skills in data analysis, attention to detail, and proficiency with tools like Excel, SQL, or data cleaning software. Knowledge of data formats, basic programming (e.g., Python or R), and understanding of data quality principles are also important for effective data cleaning tasks.

What are popular job titles related to Data Cleaning jobs in Quebec?

For Data Cleaning jobs in Quebec, the most frequently searched job titles are:

Infographic showing various Data Cleaning job openings in Quebec as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution.

Senior Applied AI Scientist

Bentley Systems

Quebec, QC • On-site

Full-time

This job post has expired today. Applications are no longer accepted.


Job description

Senior Applied AI Scientist

 

Location: Hybrid, Quebec, Canada

As a Senior Applied AI Scientist, you'll have the opportunity to develop innovative solutions in artificial intelligence (AI) for smart infrastructure, participate in the development of new products based on AI, and collaborate with an established team of Data Scientists. By virtue of its unique market positioning, our team targets a wide variety of AI-related research fields, including computer vision, graphical models, natural language processing, advanced signal processing, unsupervised learning and clustering, reinforcement learning, etc.

Responsibilities:

  • Develop AI/ML algorithms and models using accepted best practices
  • Analyze user challenges, workflows, and use cases
  • Keep yourself up to date with the relevant research and scientific literature
  • Provide a technological watch over various areas of AI/ML
  • Assist in data acquisition from various sources
  • Analyze data integrity and quality
  • Develop data cleaning strategies and prepare training datasets
  • Measure model performance and resilience
  • Prepare reports and presentations on results
  • Present results to peers, internal stakeholders, and users

Qualifications:

  • BSc, MSc, or PhD in machine learning or a related specialty
  • at least 6 years of experience doing research and development in machine learning - including deep learning and advanced techniques
  • Experience with Large Language Models, RAG, and Copilot systems
  • Experience in practical machine learning applications and development
  • Ability to develop innovative solutions in artificial intelligence to resolve concrete and complex challenges
  • Programming and use of tools related to our area of practice, such as Python, PyTorch, Scikit-learn, LangChain, Llamaindex, DSPy, GraphRAG
  • Strong problem-solving capabilities using various technologies
  • Capability to research a new topic and to learn quickly
  • Experience with major cloud providers (Microsoft Azure, Amazon AWS, ElasticSearch, etc.) and/or MLOps experience desired
  • Fluent in English

What We Offer:

  • A great Team and culture - please see our colleague video. 
  • An exciting career as an integral part of a world-leading software company providing solutions for architecture, engineering, and construction - watch this short documentary about how we got our start. 
  • An attractive salary and benefits package. 
  • A commitment to inclusion, belonging, and colleague wellbeing through global initiatives and resource groups. 
  • A company committed to making a real difference by advancing the world's infrastructure for a better quality of life, where your contributions help build a more sustainable, connected, and resilient world. Discover our latest user success stories for an insight into our global impact. 

Scientifique senior en intelligence artificielle appliquee

Lieu : Hybride, Quebec, Canada

En tant que scientifique senior en intelligence artificielle appliquee, vous aurez l'occasion de developper des solutions novatrices en intelligence artificielle (IA) pour les infrastructures intelligentes, de participer au developpement de nouveaux produits bases sur l'IA et de collaborer avec une equipe etablie de scientifiques des donnees. En raison de son positionnement unique sur le marche, notre equipe cible une grande variete de domaines de recherche lies a l'IA, notamment la vision par ordinateur, les modeles graphiques, le traitement du langage naturel, le traitement avance du signal, l'apprentissage non supervise et le regroupement, l'apprentissage par renforcement, etc.

Responsabilites :

  • Developper des algorithmes et des modeles d'IA/apprentissage automatique en utilisant les meilleures pratiques reconnues
  • Analyser les defis, les flux de travail et les cas d'utilisation des utilisateurs
  • Se tenir au courant de la recherche et de la litterature scientifique pertinentes
  • Assurer une veille technologique sur divers domaines de l'IA/apprentissage automatique
  • Aider a l'acquisition de donnees provenant de diverses sources
  • Analyser l'integrite et la qualite des donnees
  • Elaborer des strategies de nettoyage des donnees et preparer des ensembles de donnees de formation
  • Mesurer les performances et la resilience des modeles
  • Preparer des rapports et des presentations sur les resultats
  • Presenter les resultats aux pairs, aux parties prenantes internes et aux utilisateurs

Qualifications :

  • Baccalaureat, maitrise ou doctorat en apprentissage automatique ou dans une specialite connexe
  • Au moins 6 ans d'experience en recherche et developpement en apprentissage automatique, y compris l'apprentissage profond et les techniques avancees
  • Experience avec les grands modeles de langage (LLM), les systemes RAG et Copilot
  • Experience des applications et du developpement pratiques de l'apprentissage automatique
  • Capacite a developper des solutions innovantes en intelligence artificielle pour resoudre des defis concrets et complexes
  • Programmation et utilisation d'outils lies a notre domaine de pratique, tels que Python, PyTorch, Scikit-learn, LangChain, Llamaindex, DSPy, GraphRAG
  • Solides capacites de resolution de problemes a l'aide de diverses technologies
  • Capacite a faire des recherches sur un nouveau sujet et a apprendre rapidement
  • Experience avec les principaux fournisseurs de services en nuage (Microsoft Azure, Amazon AWS, ElasticSearch, etc.) et/ou experience en MLOps souhaitee
  • Maitrise de l'anglais

Ce que nous offrons :

  • Une equipe et une culture formidables - veuillez visionner notre [video sur nos collegues].
  • Une carriere passionnante au sein d'une entreprise de logiciels de premier plan mondial fournissant des solutions pour l'architecture, l'ingenierie et la construction - regardez ce [court documentaire] sur nos debuts.
  • Un salaire concurrentiel et une gamme complete d'avantages sociaux.
  • Un engagement envers l'inclusion, l'appartenance et le bien-etre des collegues par le biais d'initiatives mondiales et de groupes de ressources.
  • Une entreprise qui s'engage a faire une reelle difference en faisant progresser les infrastructures mondiales pour une meilleure qualite de vie, ou vos contributions aident a batir un monde plus durable, connecte et resilient. Decouvrez nos plus recents [temoignages de reussite de nos utilisateurs] pour avoir un apercu de notre impact mondial.

About Bentley Systems


Around the world, infrastructure professionals rely on software from Bentley Systems to help them design, build, and operate better and more resilient infrastructure for transportation, water, energy, cities, and more. Founded in 1984 by engineers for engineers, Bentley is the partner of choice for engineering firms and owner-operators worldwide, with software that spans engineering disciplines, industry sectors, and all phases of the infrastructure lifecycle. Through our digital twin solutions, we help infrastructure professionals unlock the value of their data to transform project delivery and asset performance. www.bentley.com 

Equal Opportunity Employer:

Bentley is proud to be an equal opportunity employer and considers for employment all qualified applicants without regard to race, color, gender/gender identity, sexual orientation, disability, marital status, religion/belief, national origin, caste, age, or any other characteristic protected by local law or unrelated to job qualifications.