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Research Data Analyst Jobs in Alberta (NOW HIRING)

Analyze potential risks and assist with the development of risk management recommendations ... research, data gathering techniques, and teamwork with a special emphasis on teams is required to ...

About the Department The Office of Institutional Research and Planning (OIRP) has primary responsibility for institutional strategic planning, surveying and institutional data analysis at Mount Royal.

New

The position also involves robust quantitative data analysis using modern statistical tools such as R, ensuring high-quality interpretation and dissemination of research findings. In addition, the ...

Research Scientist

Edmonton, AB ยท On-site

CA$65K - CA$73K/yr

It will involve wet lab work, computer programming for automation and data analysis, histopathology work, assisting with animal experiments, and assisting other members of the research team as needed.

The position requires a high level of performance in complex research activities for the successful execution of research projects through experimental design, data analysis, report writing, oral ...

We are proactively building a data bank for opportunities in these fields. By applying, you ensure ... Conduct research on public health issues and policies. Present findings to policymakers and ...

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Research Data Analyst information

Can I be a research data analyst with no experience?

Research data analyst roles typically require some experience with data analysis tools like Excel, SQL, or statistical software, but entry-level positions may be available for candidates with relevant education or strong analytical skills. Gaining certifications or completing relevant coursework can improve chances of starting in this field without prior work experience.

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

Research Data Analysts often encounter challenges such as data inconsistencies, missing values, and integrating data from multiple sources when working with large datasets. Addressing these challenges typically involves implementing rigorous data cleaning protocols, utilizing statistical software for data validation, and collaborating closely with research teams to understand the context behind the data. Analysts may also create documentation and standardized procedures to streamline future data processing and ensure data integrity. Staying updated with best practices in data management can help mitigate many of these issues.

What is the difference between Research Data Analyst vs Data Scientist?

AspectResearch Data AnalystData Scientist
Required CredentialsBachelor's degree in data analysis, statistics, or related field; often certifications in data toolsBachelor's or master's in computer science, statistics, or related; often advanced certifications or training
Work EnvironmentResearch institutions, universities, or corporate research divisionsTech companies, finance, healthcare, or any industry leveraging big data
Employer & Industry UsageAcademic, government, and research organizationsPrivate sector, startups, and large corporations

Research Data Analysts focus on analyzing data to support research projects, often working within academic or research settings. Data Scientists have a broader scope, including building predictive models and advanced analytics across various industries. While both roles require strong analytical skills and familiarity with data tools, Data Scientists typically have more advanced technical expertise and work on complex data modeling tasks.

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

To excel as a Research Data Analyst, you need strong analytical skills, proficiency in statistics, and a relevant degree in fields such as mathematics, statistics, or computer science. Familiarity with statistical software (e.g., R, SAS, SPSS), data visualization tools (like Tableau or Power BI), and programming languages (such as Python) is typically required. Attention to detail, critical thinking, and the ability to clearly communicate complex findings are crucial soft skills. These competencies ensure accurate data interpretation, effective collaboration with research teams, and impactful decision-making based on reliable insights.

What is a research data analyst?

A Research Data Analyst is a professional who collects, processes, and analyzes data to support research projects across various fields, such as healthcare, social sciences, or business. They use statistical tools and programming languages to interpret complex data sets and help researchers draw meaningful conclusions. Their responsibilities often include data cleaning, statistical analysis, and visualization of results for reports or publications. Research Data Analysts play a crucial role in ensuring the quality and integrity of the data used in research studies.
What job categories do people searching Research Data Analyst jobs in Alberta look for? The top searched job categories for Research Data Analyst jobs in Alberta are:
Infographic showing various Research Data Analyst job openings in Alberta as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Analyst, Tourism & Marketing Data

Travel Alberta

Calgary, AB โ€ข On-site

Full-time

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


Job description

Work. Wonders.
Get inspired - Face Your Wild in Alberta come and be a part of this amazing organization. 
At Travel Alberta, we are redefining what it means to be a tourism and economic development leader in Canada. As the provincial destination management organization, we’ve embraced an ambitious goal: doubling Alberta’s tourism sector to $25 billion in annual visitor spending by 2035. This bold vision reflects our commitment to transforming Alberta into a premier destination for both visitors and investors, driving sustainable economic growth while creating unforgettable itineraries and experiences that showcase our breathtaking landscapes, vibrant cities, and rich cultural heritage. 
Position Summary
Reporting to the Senior Manager, Business Intelligence, the Analyst, Tourism & Marketing Data is responsible for delivering high-quality analysis, research, marketing intelligence and actionable insights to support strategic and operational decision-making across Travel Alberta and the broader tourism ecosystem.
The role strengthens Travel Alberta’s ability to make evidence-based decisions by connecting tourism performance, consumer behaviour, market potential, and marketing effectiveness into clear, actionable insight. The Analyst maintains and enhances proprietary attribution models, applies advanced analytics and third-party research, and uses modern business intelligence and AI-enabled tools to measure impact, improve investment decisions, and support more effective audience targeting across destination promotion channels. 
The position also carries meaningful responsibility for data governance and quality, ensuring that data assets and analytical outputs are accurate, transparent, ethical, consistent, well-documented, and aligned with enterprise standards. Working collaboratively across internal teams, government partners, and industry stakeholders, the Analyst ensures insights are timely, relevant, and decision ready.
Key Responsibilities
1. Measurement, Modelling, Research, & Strategic Insights:
  • Acquire, clean, and analyze structured and unstructured data from multiple sources including tourism statistics, economic indicators, digital analytics, campaign performance, survey data, customer data, and third-party research datasets.
  • Apply advanced analytical techniques, including statistical modeling, segmentation, forecasting, trend analysis, predictive analytics, and scenario modeling, to generate actionable and forward-looking insights.
  • Develop, enhance, validate, and maintain attribution models that demonstrate the relationship between marketing investment and tourism outcomes.
  • Design and execute quantitative and qualitative research initiatives, including survey development, sampling approaches, qualitative tools and market intelligence studies (e.g., interviews, focus groups).
  • Support and oversee third-party research vendors, agency partners, and data providers, including project scoping, methodology review, quality assurance, and validation of outputs.
  • Translate analytical findings into compelling reports, dashboards, executive briefings, presentations, and strategic recommendations.
  • Conduct tourism economic impact assessments using approved methodologies and models.
  • Monitor tourism performance, market conditions, consumer behavior, competitive intelligence, and industry trends to identify opportunities and risks.
  • Distill consumer insights, brand research, travel intent studies, campaign effectiveness research, and market intelligence into actionable business recommendations.
  • Conduct market analysis and market potential assessments to support investment prioritization and strategic planning.
  • Use first-party and third-party data to refine customer segmentation and provide evidence-based recommendations to support audience targeting and investment optimization across channels.
  • Conduct cross-channel (paid, earned, owned and trade distribution) performance analysis to support channel level investment prioritization and strategic planning.
  • Leverage AI-enabled tools, automation, natural language querying, and advanced analytics to improve efficiency while maintaining analytical rigor and accuracy.
  • Enhance and maintenance of Travel Alberta's marketing measurement framework, ensuring documented KPIs, methodologies, calculations, baselines, and targets.
  • Evaluate effectiveness of Travel Alberta programs and provide recommendations to optimize resource allocation and strategic investments.
2. Business Intelligence & Reporting Enablement:
  • Design, develop, maintain, and optimize dashboards and reporting solutions using approved enterprise BI platforms such as Power BI, Tableau, or Domo.
  • Translate business questions into meaningful visualizations and self-serve analytical tools.
  • Ensure KPI, metric, definition, methodology, and reporting consistency across all business intelligence products.
  • Document data sources, metrics, assumptions, definitions, refresh schedules, data aggregation processes, and calculation methodologies.
  • Provide training, coaching, tools, and guidance to improve data literacy and adoption across the organization.
  • Champion data storytelling practices that improve accessibility and understanding of analytical results.
  • Collaborate with stakeholders to continuously enhance reporting functionality and decision-support capabilities.
  • Work with IT to automate reporting and streamline workflows through enterprise systems and integrated tools.
3. Data governance, Quality Assurance & Innovation:
  • Apply enterprise data governance standards across datasets, reporting, and analytical outputs.
  • Maintain standardized definitions for key tourism and marketing metrics.
  • Execute robust data validation, quality assurance, anomaly detection, and reconciliation processes.
  • Monitor data integrity and proactively identify delays, gaps, inconsistencies, and quality concerns. Lead resolution efforts with internal and external partners.
  • Maintain data dictionaries, metadata, enterprise taxonomies, methodologies, and documentation.
  • Evaluate third-party data sources and methodologies for reliability and suitability.
  • Promote ethical, responsible, and transparent use of AI-enabled analytics, solutions and analysis to ensure outputs are accurate, explainable, and unbiased. 
  • Identify opportunities to improve organizational data maturity, analytical capabilities, and innovation practices.
Required Qualifications
1. Education & Experience:
  • Bachelor’s degree in business, Marketing, Data Science, Mathematics, Statistics, a relevant technical field or equivalent combination of education and practical experience. 
  • 5+ years combined experience in marketing research, analytics, and data analysis.  
  • 5+ years of progressive experience providing strategic insights to guide marketing strategy and investment decisions, including the translation of advanced analytics into key insights that will produce business value and improve performance.  Experience working with complex, multi-source datasets and delivering actionable insights.
  • Managing or collaborating with agency partners, consultants, research vendors, or external stakeholders.
  • Experience translating advanced analytics into strategic business recommendations.
  • Supporting executive and senior leadership decision-making.
  • Knowledge of tourism industry and related data sources is considered an asset.
2. Technical & Analytical Skills:
  • Strong experience with business intelligence platforms (e.g., Power BI, Tableau, DOMO or equivalent tools), including dashboard design, data modeling, and performance optimization.
  • Solid grounding in statistical methods (e.g., regression, hypothesis testing, forecasting, predictive modeling, multivariate analysis).
  • Ability to develop forecasting, market modeling, investment optimization, and predictive analytical solutions.
  • Experience with marketing analytics, attribution modelling, campaign effectiveness measurement, consumer segmentation, and cross-channel performance analysis. 
  • Experience designing and analyzing primary research (e.g., surveys, qualitative research).
  • Experience or strong interest in leveraging AI-enabled tools (e.g., generative AI, automated analytics workflows) responsibly within analysis.
3. Data Governance & Management Expertise:
  • Understanding of data governance principles, including data quality principles.
  • Ability to document and manage data assets (data dictionaries).
  • Understanding of privacy, data protection, and responsible data use requirements.
  • Familiarity with governance frameworks (e.g., DAMA-DMBOK concepts) and their practical application.
  • Awareness of risks associated with AI-generated outputs and ability to apply appropriate controls.

Core Competencies
1. Analytical Thinking & Problem-Solving:
  • Ability to structure ambiguous problems, evaluate analytical approaches, and deliver clear, practical, evidence-based recommendations.
2. Communication & Data Storytelling:
  • Ability to translate complex analysis into clear, compelling narratives tailored to diverse audiences.
3. Collaboration & Influence:
  • Builds strong relationships and works effectively across teams to drive alignment and outcomes.
4. Organizational Agility:
  • Effectively manages multiple priorities in a fast-paced environment while maintaining quality and accuracy.
5. Innovation & Continuous Improvement:
  • Demonstrates curiosity and proactively adopts new tools, technologies, and methodologies, and continuously improves analytical practices.

*We kindly thank all agency partners, we will NOT require support to fill this role. We kindly request no phone calls nor emails*

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