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Internship R Programming Language Jobs in Calgary, AB

Strong programming skills within one or more of these development languages - C / C++ / R / Java / Python * Good experience with Large Language Model technologies * Experience within Data Engineering ...

Programming in Golang * Experience with CloudFormation Additional Information We offer: * Culture ... language courses, and a relocation program. * ForeverRemote work culture : make the most of the ...

Leverage natural language processing (NLP), LLM, and machine learning (ML) techniques, including ... Experience with programming languages such as JavaScript, Python, or Node.js. * Familiarity with ...

... language courses, and a relocation program. * ForeverRemote work culture : make the most of the ... internship opportunities. * Global impact : collaborate on impactful projects for top global ...

Experience in Python, Java, JavaScript, SQL, C#, or other programming languages * Strong customer ... Intermediate or better with Structured Query Language (SQL) for Databases * Knowledge of ...

Experience in Python, Java, JavaScript, SQL, C#, or other programming languages * Strong customer ... Intermediate or better with Structured Query Language (SQL) for Databases * Knowledge of ...

Build custom machine learning models and natural language processing systems using state-of-the-art ... Proficiency in programming languages such as Python, R, or Scala. Experience with SQL and NoSQL ...

Internship R Programming Language information

What are the key skills and qualifications needed to thrive as an R Programming Language Intern, and why are they important?

To thrive as an R Programming Language Intern, you need a solid understanding of R syntax, data manipulation, and basic statistical concepts, often supported by coursework or relevant project experience. Familiarity with tools like RStudio, version control systems such as Git, and packages like dplyr and ggplot2 is typically expected. Strong problem-solving skills, attention to detail, and the ability to communicate findings clearly help interns stand out. These skills are vital for producing reliable analyses, collaborating effectively, and contributing to data-driven decision-making within an organization.

What types of projects or tasks can I expect to work on during an R Programming Language internship?

As an R Programming Language intern, you'll typically be involved in data analysis, statistical modeling, and creating data visualizations using R. You may work on cleaning and preparing datasets, developing scripts to automate data processing, or assisting with research projects that require statistical analysis. Collaboration with data scientists, analysts, or research teams is common, and you'll likely have opportunities to present your findings or contribute to reports. This hands-on experience can help you build a strong foundation in data science and analytics, preparing you for more advanced roles in the field.

What is an Internship in R Programming Language?

An Internship in R Programming Language is a temporary position designed for students or recent graduates to gain practical experience using R, a popular language for statistical computing and data analysis. Interns typically work on real-world projects involving data manipulation, statistical modeling, and data visualization under the supervision of experienced professionals. These internships help participants develop valuable technical skills, enhance their resumes, and network within the industry. They are often available in sectors like finance, healthcare, technology, and academia, where data-driven decision-making is crucial.

What is the difference between Internship R Programming Language vs Data Analyst?

AspectInternship R Programming LanguageData Analyst
Required CredentialsBasic programming skills, often pursuing or recent graduatesBachelor's degree in related field, some certifications
Work EnvironmentInternship setting, entry-level projectsFull-time or part-time professional role
Industry UsageUsed for data analysis, visualization, and statistical tasksAnalyzes data, creates reports, supports decision-making

Internship R Programming Language focuses on learning and applying R skills in a temporary, entry-level setting, often as part of an internship. Data Analysts use R among other tools to perform ongoing data analysis in a professional environment. While internships are training roles, Data Analysts are full-time professionals with broader responsibilities.

What cities near Calgary, AB are hiring for Internship R Programming Language jobs? Cities near Calgary, AB with the most Internship R Programming Language job openings:

Machine Learning Engineer

Viridien

Calgary, AB

Full-time

Posted 25 days ago


Job description

Viridien (www.viridiengroup.com) is an advanced technology, digital and Earth data company that pushes the boundaries of science for a more prosperous and sustainable future. With our ingenuity, drive and deep curiosity we discover new insights, innovations, and solutions that efficiently and responsibly resolve complex natural resource, digital, energy transition and infrastructure challenges.

Machine Learning Engineer

Calgary, AB, Canada

Full-time

Company Description

Viridien is a global technology and HPC leader that provides data, products, services and solutions in Earth science, data science, sensing and monitoring. Our unique portfolio supports our clients in efficiently and responsibly solving complex digital, energy transition, natural resource, environmental, and infrastructure challenges for a more sustainable future.

Job Description

Viridien is looking for a Machine Learning (ML) Engineer to help us create artificial intelligence systems and tools. Machine Learning Engineer responsibilities include creating machine learning models and retraining systems. Strong skills in statistics and programming, as well as knowledge of data science and software engineering. As an integral member of our team, we highly encourage the contribution of ideas and drive in the generation of new concepts to maintain our outstanding leadership position for technology and service delivery in the marketplace.

Must be legally authorized to work in Canada.

Qualifications

Preferred Education

Degree in Computer Science, Mathematics, Physics, Electrical Engineering, or other related technical disciplines.

Key Skills & Competencies

  • Passion and aptitude for programming and technology
  • Enthusiasm for analytical and problem-solving challenges
  • Strong enterprise project experience with Machine Learning and AI
  • Strong programming skills within one or more of these development languages - C / C++ / R / Java / Python
  • Good experience with Large Language Model technologies
  • Experience within Data Engineering/Data Structuring
  • Experience creating Machine Learning Algorithms and/or Libraries.
  • Proven experience with deep learning frameworks and usage of DL libraries (TensorFlow/PyTorch)
  • Proficiency to design, build, test, and support innovative solutions.
  • Ability to define and manage project deadlines and balance workloads across a wide variety of projects.
  • Effective communication skills to keep all stakeholders regularly informed on progress.
  • Drive to innovate and have fun through collaboration and generation of ideas which lead to enhancements of our workflows.
  • Enthusiastic attitude towards learning and flexibility to adapt to new challenges or changes in direction.

Other Skills/Experience:

  • Data Visualization
  • Predictive Analysis
  • Statistical Modeling
  • Data Mining
  • Clustering & Classification
  • Data Analytics
  • Quantitative Analysis
  • Web Scraping
  • Model Development

Responsibilities:

  • Design machine learning systems
  • Collaborate with stakeholders and technology team to efficiently develop AI solutions.
  • Research and implement appropriate ML algorithms and tools.
  • Develop machine learning applications according to requirements.
  • Provide support to achieve successfully deployed models at conclusion of projects.
  • Plan and manage data analysis workflows.
  • Create charts, graphs, maps, and data visualization tools to provide an accessible way to see/understand trends, patterns, outliers, in data.
  • Select appropriate datasets and data representation methods.
  • Run machine learning tests and experiments.
  • Train and retrain systems when necessary.
  • Extend existing ML libraries and frameworks.

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