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Data Analyst Jobs in Quebec (NOW HIRING)

Pension Analyst

Montreal, QC · On-site +1

CA$39K - CA$74K/yr

Work with pension databases to ensure data accuracy * Attend internal training sessions to stay ... Strong analytical and mathematical skills * A strong client service focus with exceptional ...

Si tu cherches un role uniquement en analyse d'affaires ou en visualisation de donnees, ce n'est pas celui-ci. CE QUE TU VAS FAIRE Developpement et integration * Developper et maintenir des ...

Nous cherchons des Specialistes des données / Data specialist , pour le compte de notre partenaire ... Analyser la performance manufacturière et l'adhérence aux processus * Identifier les causes ...

Un rôle de Data Engineer pur axé uniquement sur l'ingestion et l'infrastructure. * Un rôle de Business Analyst concentré exclusivement sur la définition des besoins * Un rôle de BI Developper ...

Pourriez-vous etre l'ingenieur(e) en analyse numerique a St-Bruno que nous recherchons ? Votre futur role Relevez un nouveau defi et mettez a profit votre expertise en ingenierie et analyse de ...

The Senior Data Analyst will support a major Department of National Defence (DND) defence acquisition client in advancing their Digital Engineering, Modeling and Simulation (DEM&S) ecosystem. This ...

The Senior Data Analyst will support a major Department of National Defence (DND) defence acquisition client in advancing their Digital Engineering, Modeling and Simulation (DEM&S) ecosystem. This ...

... automatisation et la data. En forte croissance, nous traitons des milliers de demandes de ... Tu analyses un fort volume de dossiers de crédit, gères un flux important d'appels avec les ...

Nous accompagnons nos clients avec des solutions sur mesure allant de l'intégration de l'IA à la modernisation des ERP et CRM, en passant par l'analyse avancée des données. Notre mission est ...

Showing results 41-60

Data Analyst information

What is the difference between Data Analyst vs Data Scientist?

AspectData AnalystData Scientist
Required CredentialsBachelor's degree in statistics, mathematics, or related field; often certifications in data analysis toolsBachelor's or master's in computer science, statistics, or related; often advanced certifications or degrees
Work EnvironmentBusiness settings, focusing on data reporting and visualizationResearch and development environments, focusing on predictive modeling and complex algorithms
Employer & Industry UsageRetail, finance, healthcare, and marketing companiesTech firms, research institutions, and large enterprises

While both roles analyze data, Data Analysts primarily focus on interpreting existing data to generate reports and insights, whereas Data Scientists develop predictive models and advanced algorithms to forecast trends and solve complex problems.

Can I learn a data analyst in 3 months?

A data analyst role requires skills in data manipulation, statistics, and tools like Excel, SQL, and Python or R. While three months can provide a foundational understanding through intensive training or bootcamps, gaining proficiency typically takes longer with consistent practice and real-world experience.

What are some common challenges data analysts face when working with large datasets, and how are they typically addressed?

Data Analysts often encounter challenges such as data quality issues, missing or inconsistent values, and slow processing times when handling large datasets. These challenges are typically addressed by implementing data cleaning routines, using advanced data management tools, and leveraging programming languages like Python or R for efficient data manipulation. Collaboration with database administrators and IT teams is also common to ensure data integrity and optimize data storage solutions. Staying updated with best practices in data wrangling and visualization helps Data Analysts deliver accurate and actionable insights.

What work does a data analyst do?

A data analyst collects, processes, and analyzes large datasets to identify trends, patterns, and insights that support business decision-making. They use tools like Excel, SQL, and data visualization software to interpret data and communicate findings to stakeholders. Strong analytical skills and attention to detail are essential for this role.

What are the key skills and qualifications needed to thrive as a data analyst, and why are they important?

To thrive as a Data Analyst, you need strong analytical skills, proficiency in statistics, and a relevant degree such as in mathematics, statistics, or computer science. Familiarity with data analysis tools like SQL, Excel, Python or R, and experience with visualization platforms such as Tableau or Power BI are typically required. Strong problem-solving abilities, attention to detail, and effective communication skills help analysts interpret data insights and present findings clearly to stakeholders. These skills are crucial for transforming raw data into actionable business insights that drive informed decision-making.

What are top 3 skills for a data analyst?

The top three skills for a data analyst are proficiency in data manipulation and analysis tools like Excel, SQL, and statistical software; strong analytical and problem-solving abilities; and effective communication skills to present insights clearly. Familiarity with data visualization tools such as Tableau or Power BI is also highly valuable. These skills enable data analysts to interpret complex data and support decision-making processes.

What does a data analyst do?

A Data Analyst is responsible for collecting, processing, and analyzing data to help organizations make informed business decisions. They use statistical tools and software to interpret data sets, identify trends, and create visual reports. Data Analysts often collaborate with other departments to provide actionable insights and support strategic planning. Their work helps organizations optimize operations, track performance, and solve business problems using data-driven approaches.

What are the most commonly searched types of Data Analyst jobs in Quebec?

The most popular types of Data Analyst jobs in Quebec are:

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

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

What job categories do people searching Data Analyst jobs in Quebec look for?

The top searched job categories for Data Analyst jobs in Quebec are:

What cities in Quebec are hiring for Data Analyst jobs?

Cities in Quebec with the most Data Analyst job openings:

Infographic showing various Data Analyst job openings in Quebec as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.

Senior Business Data Officer-Client & Account Data Transformation

Societe Generale

Montreal, QC • On-site

Full-time

Re-posted yesterday


Job description

The Client Lifecycle & Digitalization Department (CLD) resides as part of the Wholesale Clients Technology & Operations division within Global Banking and Investor Solutions.

CLD's mission is to deliver a state-of-the art digital platform, targeting both users and clients in covering pre-trade, execution and post-trade activities. Additionally, our mission is to grow our internal client knowledge and deliver a user-friendly experience through the client lifecycle, while mitigating risk.
Within CLD in the Americas, the REF team (Referential and Regulatory & Tax data) oversees Referential Client Data, Regulatory & Tax Client Data and Data Quality initiatives across all of CLD.

We are undertaking a major transformation of our Account Management processes across Principal businesses. Today's onboarding and account lifecycle workflows rely on multiple back-office systems BPS/Impact for Principal activities-combined with manual coordination, Excel templates, and unstructured email exchanges. This fragmentation creates operational inefficiencies and limits our ability to automate and scale.

The Senior Business Data Officer plays a critical role in the modernization of account management, onboarding, and client reference data processes.

This role combines Operations and data expertise, focusing on improving end to end account lifecycle workflows, strengthening data quality controls, and enabling scalable, digital, and compliant solutions.

Daily Operational Support
    Ensures accuracy, consistency, and control of client and account static data across core platforms.
    Supports BAU operations, issue resolution, and regulatory requirements.

Subject Matter Expertise (SME) Across Platforms
    Leads initiatives to replace fragmented, manual processes with structured data flows, standardized models, and automated controls.
    Serves as a central point of expertise for multiple back office systems.

Process Transformation & Optimization
    Analyzes onboarding, maintenance, and closure workflows to identify inefficiencies.
    Redesigns processes and transitions manual, email driven activities into structured, digital solutions.

Cross Functional Bridge & Delivery Owner
    Connects business, operations, technology, compliance, and vendors to translate complex needs into clear functional requirements.
    Owns delivery from analysis through go live, driving continuous improvement and strengthening account lifecycle governance.

Responsibilities:

Account Lifecycle & Process Transformation
    Analyze current account onboarding, creation, maintenance, and closure processes across multiple back office systems (BPS/Impact, AccountHub, Maestro, etc.).
    Identify operational inefficiencies, manual handoffs, unstructured data dependencies, and data quality risks.
    Redesign workflows to support standardized, digital, and scalable account lifecycle management.
    Support the migration from email, spreadsheets, and PDFs to structured data capture and workflow driven processes.

Data Quality, Controls & Referential Data Management
    Ensure accuracy, completeness, and consistency of client and account static data across all core systems.
    Maintain and enhance data quality controls, including periodic reviews, exception analysis, and remediation efforts.
    Lead and contribute to initiatives such as: 
    Quality driven data reviews (e.g., Business address remediation)
    Reconciliation between systems (e.g., BPS vs. Maestro)
    Migration of manual and legacy controls into centralized data quality platforms (IDQ)
    Serve as a key contributor to data standardization and reference data harmonization efforts.

Systems, Integration & Platform Expertise
    Map account attributes requirements across product specific systems.
    Support the centralization of account data into AccountHub, the strategic account management platform.
    Partner closely with IT teams to define: 
    Data models and attribute definitions
    Validation rules and business logic
    Integration flows and APIs
    Contribute to workflow orchestration initiatives, including: 
    BOLT (Agency account lifecycle requests)
    OCTO (Principal account lifecycle requests)

Stakeholder & Vendor Collaboration
    Act as a bridge between Front Office, Operations, KYC/Onboarding, Compliance, Technology, and offshore teams.
    Lead workshops and requirement gathering sessions with internal teams and external vendors (e.g., Broadridge).
    Translate complex operational account management needs into clear functional specifications.
    Provide subject matter guidance to offshore teams, ensuring procedures are understood, followed, and consistently applied.

Delivery, Oversight & Leadership
    Drive initiatives from analysis through design, build, testing, and go live.
    Produce high quality documentation, including BRDs, functional specifications, data mappings, and SOPs.
    Support UAT planning and execution, ensuring solutions meet business, regulatory, and operational requirements.
    Provide ongoing oversight of BAU activities, issue escalation, and continuous process improvement.
    Mentor and guide team members, promoting knowledge sharing, training, and strong data discipline.

Required
    5 years of experience as a Business Data Officer or Business Data Officer within financial services.
    Strong knowledge of account lifecycle management, client reference data, and KYC/AML processes.
    Hands on expertise with back office platforms such as IMPACT, BPS and related data repositories.
    Proven experience in data quality management, controls, remediation, and regulatory driven initiatives.
    Ability to analyze complex data sets and reconcile discrepancies across multiple systems.
    Strong communication skills, with the ability to work effectively with both technical and non technical stakeholders.

Preferred
    Experience with AccountHub or similar centralized account management platforms.
    Familiarity with workflow orchestration tools and data quality platforms (e.g., IDQ).
    Experience working with external vendors (e.g., Broadridge).
    Background in digital transformation, automation, or large scale data standardization initiatives.

Qualification:

    Bachelor's Degree
    Desired / Plus: MBA
 

LANGUAGE: 

Ability to communicate in English, both orally and in writing, is a requirement as the person in this position will need to collaborate regularly with colleagues and partners in the United States. 

Due to US Federal Securities law that may apply to this position, candidates who will apply for this position may be required to submit to an enhanced background screening, including the collection of their fingerprints by a third-party vendor selected by the Financial Industry Regulatory Authority ("FINRA").