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Data Science And Analytics Jobs in Edmonton, AB (NOW HIRING)

Targeted Talent

Data Scientist

Edmonton, AB · Remote

... Science utilizing R (purrr, tidyr, dplyr, tibble, & the tidyverse) * Strong analytical skills working with unstructured data sets * Knowledge of relational (PostgreSQL, MySQL, etc.) and non ...

Targeted Talent

Data Scientist

Edmonton, AB · Remote

... Science utilizing R (purrr, tidyr, dplyr, tibble, & the tidyverse) * Strong analytical skills working with unstructured data sets * Knowledge of relational (PostgreSQL, MySQL, etc.) and non ...

National Bank

Senior Data Scientist

Edmonton, AB · On-site

Frame high-impact analytics and artificial intelligence mandates with partners, clarify business needs, and translate them into concrete data science solutions. * Design, develop, validate, and ...

TELUS

Data Scientist

Edmonton, AB

Document analytical findings and architectural decisions clearly, and mentor team members on data best practices. Qualifications What you bring * Master's degree in Computer Science, Data Science ...

Targeted Talent

Senior Data Scientist

Edmonton, AB · Remote

... Science utilizing R (purrr, tidyr, dplyr, tibble, & the tidyverse) * Strong analytical skills working with unstructured data sets * Knowledge of relational (PostgreSQL, MySQL, etc.) and non ...

Targeted Talent

Senior Data Scientist

Edmonton, AB · Remote

... Science utilizing R (purrr, tidyr, dplyr, tibble, & the tidyverse) * Strong analytical skills working with unstructured data sets * Knowledge of relational (PostgreSQL, MySQL, etc.) and non ...

TELUS

Staff Applied AI/ML Scientist

Edmonton, AB

... data science with your strong ML Ops and software development skills to automate and facilitate data exploration, analytics, machine learning model development, training and deployment and will ...

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All JobsData Science And Analytics JobsData Science And Analytics Jobs in Edmonton, AB

Data Science And Analytics information

What work can I do with data science?

Data science and analytics professionals analyze data to uncover insights, build predictive models, and support decision-making across various industries. They work with tools like Python, R, and SQL, and often need skills in statistics, data visualization, and machine learning to perform tasks such as data cleaning, reporting, and developing algorithms.

Is 40 too late for data science?

Data science and analytics roles value skills and experience over age; many professionals transition into the field later in life. Gaining proficiency in programming languages like Python or R, and understanding data tools, can help offset age concerns. Continuous learning and relevant certifications can improve job prospects regardless of age.

What are data science and analytics jobs?

Data science and analytics jobs involve analyzing large datasets to extract insights, support decision-making, and solve business problems. These roles typically require skills in programming, statistics, and tools like Python, R, or SQL, and often involve creating reports or predictive models. Professionals in these fields work in various industries such as finance, healthcare, and technology, with responsibilities that include data cleaning, visualization, and modeling.

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

To thrive in Data Science and Analytics, you need strong skills in statistics, data manipulation, and programming, typically backed by a degree in computer science, mathematics, or a related field. Proficiency with tools like Python, R, SQL, and data visualization platforms such as Tableau, along with knowledge of machine learning frameworks, is highly valued. Strong problem-solving ability, critical thinking, and effective communication skills help translate complex data findings into actionable business insights. These skills are crucial for turning raw data into strategic decisions that drive organizational success.

What are Data Science and Analytics?

Data Science and Analytics refer to the fields that focus on extracting meaningful insights from large and complex data sets. Data Science combines statistics, computer science, and domain knowledge to analyze data, build predictive models, and support data-driven decision-making. Analytics, which is a core part of data science, involves examining data to discover trends, patterns, and correlations that can help organizations solve problems or improve processes. Professionals in these fields use tools such as Python, R, SQL, and machine learning algorithms to analyze data and communicate findings to stakeholders.

What can I do with a data science and analytics degree?

A data science and analytics degree prepares individuals for roles such as data analyst, data scientist, business intelligence analyst, or machine learning engineer. Graduates can work in industries like finance, healthcare, marketing, and technology, utilizing skills in programming, statistical analysis, and data visualization tools like Python, R, SQL, and Tableau.

What is the difference between Data Science And Analytics vs Data Analysis?

AspectData Science And AnalyticsData Analysis
Required SkillsStatistical modeling, programming, machine learningData cleaning, descriptive statistics, visualization
Work EnvironmentCross-functional teams, R&D, predictive modelingBusiness reporting, dashboards, ad hoc analysis
Tools & TechnologiesPython, R, SQL, Hadoop, SparkExcel, SQL, Tableau, Power BI
Industry UsageTech, finance, healthcare, marketingRetail, finance, healthcare, operations

Data Science And Analytics involves advanced techniques like machine learning and predictive modeling, often requiring programming skills. Data Analysis focuses on interpreting existing data through descriptive statistics and visualization for decision-making. Both roles are essential but differ in complexity and scope.

What are some common challenges faced by data science and analytics professionals when working with cross-functional teams?

Data science and analytics professionals often collaborate with colleagues from diverse backgrounds such as engineering, marketing, and business operations. One common challenge is translating complex analytical findings into actionable insights that non-technical stakeholders can easily understand. Additionally, aligning project objectives and timelines across teams can require strong communication and project management skills. Overcoming these challenges is essential for ensuring that data-driven solutions are effectively implemented and contribute to organizational goals.
Data Science And Analytics jobs near you
Infographic showing various Data Science And Analytics job openings in Edmonton, AB as of July 2026, with employment types broken down into 33% Full Time, 33% Part Time, and 34% Contract. Highlights an 33% In-person, and 67% Remote job distribution.

Data Science Student

PCL Construction

Edmonton, AB

Other

Re-posted 16 days ago

PCL Construction rating

7.0

Company rating: 7.0 out of 10

Based on 16 frontline employees who took The Breakroom Quiz

Job description

The future you want is within reach. 
At PCL, we build the places where life happens and find camaraderie in the process. We're a community of builders committed to building better communities. That's why we're always looking ahead, and not just to the next project or what's next in our industry.  
We're also looking at what's next for you and how we can help you build a career you're proud of. As a student at PCL, you will get the opportunity for challenging work assignments in a supportive work environment which promotes personal and professional growth.  


We are seeking a Data Science Student for our Canadian Industrial Division district office in Edmonton, AB, that is availablefor 8 or 12 months starting in September, 2026.This position willbe under the direct supervision of the Manager, Data Science. 

Remote work not available for this position.

 
As a Data Science Student, you will contribute to our team by: 

Responsibilities

   Gain proficiency in exploratory data analysis, perform it, and present insights. 
   Prepare data sets for visualization and machine learning modeling. 
   Train machine learning systems using data annotation and benchmarking techniques. 
   Help your colleagues assess AI/ML model performance and propose paths for potential improvement. 
   Prepare data visualizations using industry-leading tools to summarize results for stakeholders. 
   Document your results - tell the story of the work, the successes, and the lessons-learned for posterity. 
   Keep an open mind, in order to utilize your unique skills and your determination when other opportunities arise. 


This position has a twist. Contingent on successful early work, the team member will have a chance to build their portfolio through a capstone project. For the final two months, a portion of their time will be focused on a design-focused initiative, of value to PCL, of their choosing. You'll be supported while you: 
   Develop a proposal 
   Engage with the right people to inform your work 
   Build your prototype or visualization 
   Assess and present the results 

Qualifications

   Currently enrolled in a postsecondary program 
   You should be an outstanding bachelor's or mathematics student in engineering, computing, or mathematical sciences. Alternatively, you could be pursuing an MSc in a quantitative field. If your field of study differs, apply: we'd like to hear why you'll be a good fit regardless. 
   Analytical skills - ability to quickly analyze data to identify and visualize key insights - as evidenced by coursework, projects, or research requiring the analysis of large datasets. 
   Coursework in statistics. Applied statistics and probability are the focus of the position: if you can converse about regression models, and clustering approaches, you'll be fine. 
   Prior exposure to a statistical or scientific programming environment is helpful. If you don't have it, you'll become familiar while you're with us.  We have a bias for open source tech, and work with the Python scientific stack, R, PowerBI, and various data pipeline tools. 
   Excellent oral and written communication skills will help. You'll work with both experts in the field and business staff, so you'll find it important to be able to communicate appropriately with both as needed. 

Next Step: 
Please note that candidates who have been selected to move forward to the next stage of the recruitment process will receive an email to complete a short online video interview. 
PCL is an innovative, employee-owned company comprised of people who find passion in their profession and take pride in doing great work every day. Our work powers the infrastructure and utilities that are essential to daily life and our projects are the scene of vacations, careers, education and healing. We are consistently ranked among the best companies to work for because we are committed to supporting and developing our teams.

The PCL Companies celebrate diversity and are proud to be an equal opportunity employer. We are committed to creating equitable opportunities and an inclusive environment for all employees and applicants.  We make employment-related decisions without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, age, disability or veteran status.
Should you require an accommodation during the application process, please contact us at careers@pcl.com with the position and location you are interested in.  
Together, we can build success and a better future. Let's get started! 
 

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