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Data Science Fall Internship Jobs in Calgary, AB

Delivery Engineer - Canada

Calgary, AB ยท Remote

CA$80K - CA$120K/yr

Bachelor's degree in Computer Science, Engineering or a related field is required; a Master ... data technologies, or machine learning through coursework, internships, or project experience is a ...

Bachelor's degree in Computer Science, Engineering or a related field is required; a Master ... data technologies, or machine learning through coursework, internships, or project experience is a ...

Workday Analyst - Financials & Projects

Calgary, AB ยท On-site +1

CA$85K - CA$100K/yr

Prior exposure to Workday or another ERP system (through coursework, an internship, or on-the-job ... unites science, data and practical expertise to deliver solutions that strengthen our clients ...

Showing results 21-40

Data Science Fall Internship information

What is a data science fall internship?

A Data Science Fall Internship is a temporary, structured work experience offered by organizations during the fall semester, designed for students or recent graduates interested in data science. Interns typically work on real-world projects involving data collection, analysis, machine learning, and visualization under the guidance of experienced data scientists. This internship provides hands-on experience, exposure to industry tools and techniques, and helps participants build valuable skills for future careers in data science. It also offers networking opportunities and a chance to explore potential career paths within the field.

What types of projects can I expect to work on during a data science fall internship?

As a Data Science Fall Intern, you can expect to work on projects involving data cleaning, exploratory data analysis, and the development of predictive models using real-world datasets. Interns often collaborate with full-time data scientists and cross-functional teams to solve business problems, such as improving user engagement, optimizing processes, or generating actionable insights from large data sets. You may also participate in regular team meetings, present findings, and contribute to ongoing research or tool development. This hands-on experience helps you build both technical and communication skills within a dynamic and supportive environment.

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

To thrive as a Data Science Fall Intern, you generally need a solid foundation in statistics, programming (often Python or R), and data analysis, typically supported by coursework or experience in computer science, mathematics, or related fields. Familiarity with tools like pandas, scikit-learn, SQL, and data visualization libraries, as well as version control systems like Git, is highly valued. Strong problem-solving abilities, attention to detail, and effective communication skills help interns interpret data insights and collaborate with team members. These competencies are essential for producing actionable analyses and contributing meaningfully to data-driven projects in a short-term, fast-paced internship environment.

What is the difference between Data Science Fall Internship vs Data Analyst Intern?

AspectData Science Fall InternshipData Analyst Intern
Required CredentialsEnrolled in or recent graduate of a related field (e.g., Data Science, Computer Science, Statistics)Enrolled in or recent graduate of a related field (e.g., Data Analysis, Business, Statistics)
Work EnvironmentTech companies, startups, research labs, often collaborative and project-basedBusiness firms, consulting agencies, often focused on reporting and data visualization
Employer & Industry UsageUsed by tech firms, finance, healthcare, and academia for entry-level talentCommon in corporate, marketing, and consulting sectors for supporting decision-making

The Data Science Fall Internship and Data Analyst Intern roles share similarities in required education and work environment but differ in focus. Data Science internships emphasize machine learning, programming, and statistical modeling, while Data Analyst internships focus more on data visualization, reporting, and business insights. Both are valuable entry points into data careers, often overlapping in skills but serving different industry needs.

Infographic showing various Data Science Fall Internship job openings in Calgary, AB as of August 2026, with employment types broken down into 21% Internship, 35% Full Time, 41% Part Time, and 3% Contract. Highlights an 82% In-person, 5% Hybrid, and 13% Remote job distribution.

Delivery Engineer - Canada

DataVisor

Calgary, AB โ€ข Remote

CA$80K - CA$120K/yr

Full-time

Medical, PTO

Re-posted 2 days ago


Job description

DataVisor is the world’s leading AI-powered Fraud and Risk Platform that delivers the best overall detection coverage in industry. With an open SaaS platform that supports easy consolidation and enrichment of any data, DataVisor's solution scales infinitely and enables organizations to act on fast-evolving fraud and money laundering activities in real time. Its patented unsupervised machine learning technology, advanced device intelligence, powerful decision engine and investigation tools work together to provide guaranteed performance lift from day one. DataVisor's platform is architected to support multiple use cases across different business units flexibly, dramatically lowering total cost of ownership, compared to legacy point solutions. DataVisor is recognized as an industry leader and has been adopted by many Fortune 500 companies across the globe.

Our award-winning software platform is powered by a team of world-class experts in big data, machine learning, security, and scalable infrastructure. Our culture is open, positive, collaborative, and results-driven. Come join us!

Position Overview:

We are seeking a Delivery Engineer to join our Delivery team. The ideal candidate will lead client communications and drive end-to-end project delivery, while designing and implementing innovative integration solutions that meet both technical and business requirements.This role requires close collaboration with clients, sales teams, and internal stakeholders to ensure successful project outcomes. As a technical delivery leader, the TPM will own and manage all engineering work streams, coordinating across teams to keep projects on schedule and aligned with scope. The role is hands-on, requiring the ability to contribute directly to technical implementation and problem-solving as needed.

Key Responsibilities:

  • Manage and drive client communications throughout the entire project delivery, align different client stakeholders, ensure project is delivered successfully without delay.
  • Work closely with clients, sales teams, and other stakeholders to ensure successful project outcomes.
  • Understand the client's product and business logic to recommend the best solution that addresses specific client needs. Provide strong solution and consulting services.
  • Take the project management role to ensure the client onboarding project runs as expected and under control.
  • Provide technical expertise and guidance throughout the implementation and deployment phases, to integrate with the client systems.
  • Work closely with product and engineering teams to ensure seamless integration of new features and technologies into existing systems.
  • Stay updated on financial services industry trends and emerging technologies to continuously improve our solutions and offerings.
  • Conduct presentations and demonstrations of proposed solutions to clients and stakeholders.

Requirements

Qualifications:

  • Bachelor’s degree in Computer Science, Engineering or a related field is required; a Master’s degree in a business-related discipline (e.g., MBA, MIS, Information Systems, Management, or Analytics) is preferred.
  • Basic understanding of software development, system architecture, and system integration concepts; exposure to SaaS platform data integration is a plus.
  • Strong verbal and written communication skills, with the ability to clearly explain technical concepts to both technical and non-technical audiences.
  • Enjoys working with clients and stakeholders, with a service-oriented mindset and interest in client-facing responsibilities.
  • Ability to work collaboratively in a team environment and support multiple projects under guidance and supervision.
  • Demonstrates strong problem-solving skills, attention to detail, and a willingness to learn in a fast-paced environment.
  • Familiarity with anti-fraud concepts in the financial services or internet industry is a plus.
  • Exposure to real-time computing, big data technologies, or machine learning through coursework, internships, or project experience is a plus.

Benefits

1. Health Insurance, PTO, stock option

2. The expected salary range for this role is CAD $80,000 – $120,000 per year, depending on experience, qualifications, and location. Final compensation will be determined based on job-related skills and business needs