Priority may be given to the following designated employment equity groups: women, Indigenous Peoples* (First Nations, Inuit and Métis), persons with disabilities and racialized persons*.

- The Employment Equity Act, which is under review, uses the terminology Aboriginal peoples and visible minorities.

OrganizationalUnit: Digital Technologies Language Requirements: English or French Due to the nature of the work and operational requirements, this position may be eligible for a limited hybrid work arrangement (combination of working onsite and telework). At the NRC, we recognize that Indigenous candidates may have important connections to their communities and you may be eligible for an exception to this work arrangement. To learn more about these options, please contact the NRC Hiring team using the contact information below.

Client

Engagement and Project Scoping Meet with Canadian SMEs to understand their business context, operational challenges, data assets, and decision‑making needs. Help clients clarify and refine business problems into feasible data science, analytics, or AI projects. Contribute to project scoping, including technical approaches, work plans, timelines, assumptions, risks, and deliverables.

Communicate clearly with clients throughout the project lifecycle, including managing expectations and explaining analytical findings.

Applied Data

Science and Statistical Modelling Acquire, clean, process, explore, and analyze structured and unstructured data. Develop statistical, machine learning, and analytical models to address client problems. Apply appropriate methods such as regression, classification, clustering, forecasting, optimization, natural language processing, simulation, or other relevant techniques.

Evaluate model performance, uncertainty, limitations, and practical usefulness. Coding, Reproducibility and Delivery Write clear, efficient, maintainable code in Python, R, or similar languages. Develop reproducible analytical workflows using notebooks, scripts, version control,



and good documentation practices.

Build prototypes, dashboards, data pipelines, reports, and reusable analytical tools. Balance rigour with practical delivery timelines in a project‑based setting. Present technical findings to both technical and non‑technical audiences.

Prepare concise written deliverables, including summaries, reports, presentations, and recommendations in plain language. Work collaboratively in small teams of data scientists, software developers, data engineers, researchers, and business development staff. Manage multiple priorities and deadlines across client‑facing projects.

Stay current with emerging data science, machine learning, and AI practices. Contribute to NRC practices for responsible, transparent, and reproducible AI. Applicants must demonstrate within the content of their application that they meet the following screening criteria in order to be given further consideration as candidates: A master’s degree in data science, statistics, computer science, mathematics, engineering, operations research, economics, or another relevant field; A bachelor’s degree in a relevant field combined with significant experience in applied data science, statistics, analytics, machine learning, or related work may be considered.

Assets

Experience with cloud platforms such as Azure, AWS, or GCP.

Experience with MLOps, containerization, CI/CD, model deployment, or production analytics workflows.

Experience with natural language processing, generative AI, computer vision, optimization, forecasting, or simulation. Applying data science, statistical analysis, machine learning,



or advanced analytics to solve real‑world problems. Cleaning, processing, exploring, and analyzing data from diverse sources.

Coding in Python, R, or a similar language for data analysis, modelling, or automation. Communicating technical findings to non‑technical audiences through presentations, reports, visualisations, or client briefings. Working in teams to deliver projects within defined timelines.

Strong knowledge of statistical, mathematical, and machine learning methods and their application to practical problems. Ability to writing clean, reproducible, and maintainable production‑ready code.

Research

Technician/Technologist - Communication (Level 3) Research Technician/Technologist - Creative thinking (Level 3) Research Technician/Technologist - Results orientation (Level 3) Research Technician/Technologist - Client focus (Level 3) Research Technician/Technologist - Teamwork (Level 3) Salary determination will be based on a review of the candidate’s expertise, outcomes and impacts of their previous work experience relative to the requirements of the level. NRC employees enjoy a wide‑range of competitive benefits including a robust pension plan, comprehensive health and dental coverage, disability and life insurance, office closure at the end of December, and additional supports to enhance your well‑being throughout your career and beyond. Anything is possible at the NRC, named in 2026 one of Canada’s Top Employers for Young People, Top Employer in the National Capital Region and Forbes Canada’s Best Employers!

Every day we explore new ideas through innovative research and help companies discover possibilities that impact Canada’s future and the world. You’ll collaborate across multiple fields and with the brightest minds to find creative solutions. Relocation assistance will be determined in accordance with the NRC's directives.

Preference will be given to Canadian citizens and permanent residents of Canada.

📌 Data Scientist - Fulltime (Ottawa)
🏢 National Research Council of Canada
📍 Ottawa