The opportunity:

The Canadian Resident Matching Service (CaRMS), is seeking a driven, engaged, and inquisitive Junior Data Scientist with a passion for building critical data infrastructure and applying data science to support decision-making. Reporting to the Lead Data Scientist, this position will support CaRMS’ data strategy through the design, implementation, maintenance, and expansion of a new data platform using a data stack employing PostgreSQL and Python (SQLAlcemy/SQLModel, Dagster, and FastAPI).

This is a full-time, permanent position that is fully remote . The successful candidate must be based in Canada and have the ability and willingness to travel if required. The language requirement for this role is either English essential or bilingual (English and French) . Occasional overtime may be necessary to meet critical deadlines.

Your impact:

CaRMS uses data to answer important internal and external stakeholder questions related to policy, match participant preferences, and match outcomes generated by the matching algorithm. As your domain knowledge of the matching business develops, you will increasingly contribute data-driven insights for both internal teams and external clients.

As part of a small, collaborative team , you will be heavily involved in data engineering and hands-on technical work . You will contribute to the design, implementation, and operation of core data infrastructure, including systems that:

• Update and maintain the corporate Data Warehouse
• Exchange data with the matching software
• Generate data products and services

Initially, your primary focus will be the modernization of the internal platform used to run the matching algorithm . Working closely with the Lead Data Scientist, you will help rebuild and enhance ETL processes that prepare inputs for the match algorithm and process its outputs.

The role and responsibilities:

Data Engineering

• Designing, implementing, and operating critical data infrastructure, including systems for updating the corporate Data Warehouse, passing information to and from our matching software, and generating data products (operational reporting, data contracts, match statistics, etc.)
• Migrating ETL associated with passing information to and from the matching software from Informatica PowerCenter to new PostgreSQL/Python-based data platform (PostgreSQL, SQLAlcemy / SQLModel, Dagster, and MkDocs)
• Developing internal matching platform API (using FastAPI) to run ETL associated with the matching software and help application developers use it
• Consolidating overlapping SQL views across data products to ensure consistency
• Developing modular Python-based reporting framework for producing data contracts, operational reporting, and custom data requests

Data Science

• Maintaining and extending match simulation software and conducting “what-if” scenario analysis for stakeholders in collaboration with the Lead Data Scientist
• Contributing to R markdown/Quarto-based "insight" research pieces for internal and external stakeholders
• Helping our stakeholders understand applicant and employer preferences (preference modeling)
• Developing better ways to help our clients find their ideal candidates/residency positions (for use in our broader web application)

Qualifications:

• Four-year degree in data science, economics, computer science, engineering, applied mathematics, statistics or equivalent work experience.
• Very strong proficiency in Python and advanced SQL skills is required.
• 3-5 years of experience with Python-based data engineering / data science packages (particularly SQLAlchemy/SQLModel, pandas, Dagster, FastAPI, and LangChain).
• Experience using cloud data storage (AWS S3), PostgreSQL-compatible database services (i.e., fully managed through RDS / Aurora, or self-managed on Amazon EC2), and compute (EC2, ECS, Fargate) is very highly valued.
• Significant experience with relational database systems (e.g., Oracle, PostgreSQL, etc.).
• Deep understanding of data management concepts associated with designing, building, maintaining, and extending an Enterprise Data Warehouse.
• Use of version control (Git) and test-based development practices should be strongly engrained in your workflow
• Practical experience with any of the following is valued:
• Implementing semantic search and Q&A on documents.
• Computational statistics, particularly resampling techniques .
• Matching algorithms
• Informatica PowerCenter .
• Using Quarto/R markdown to produce reproducible reporting.
• Developing and supporting dashboards (e.g., Tableau, MS Power BI , etc.).
• Jira and Confluence collaboration tools.

The successful candidate:

Our ideal candidate requires very strong Python-based data engineering skills. You are a highly organized, detail-oriented, and analytical individual who is a self-starter with a high degree of initiative. You are internally driven to continually hone your data engineering/data science skills. You can produce strong results within tight deadlines. You have strong communication skills (in English) and can clearly convey pertinent information to internal stakeholders at the appropriate level of detail. Your strong team orientation enables you to work with multiple departments to meet their data needs. You have the exceptional problem-solving skills required to deliver effective data solutions for our clients. You may be an early career data engineer looking to break into data science.

How do you stand out?

To stand out, you must show us your work. We are modernizing our infrastructure using PostgreSQL, SQLAlchemy/SQLModel, Dagster, and FastAPI. We have made public-facing CaRMS data scraped from our website available in an easily consumable format on the personal GitHub account of our Lead Data Scientist, Derek Nokes (dnokes/Junior-Data-Scientist: Public-facing CaRMS data scraped from the CaRMS website.). Use it to show us your data engineering, data science, and/or visualization skills. Use our stack and show us what you can do! Build something, provide your project GitHub repository link in your application, get an interview, and present your work to us.

About CaRMS:

The Canadian Resident Matching Service (CaRMS) is a national, independent, not-for-profit organization that provides digital solutions and expertise that matches medical students with training opportunities in Canada.

CaRMS’ mission is to serve as trusted stewards, builders, and innovators of data-informed application and matching services. Our vision is to provide the best possible outcomes for both applicants and faculty through safe, fair, and equitable application and matching systems.

Established in 1970 to provide a fair, objective, and transparent process, CaRMS works with the medical education community, medical schools, and residents/students to provide the digital platform, mathematical algorithm, and knowledge that matches students with medical residency training opportunities.

CaRMS is a client service-focused organization relying on a caring and committed team for our success.

What we offer:

CaRMS values an equitable, diverse, and inclusive workforce. We offer a collaborative and enjoyable hybrid work environment that focuses on continuous quality improvement (CQI), professional growth opportunities, a comprehensive benefits package, and an industry-leading defined contribution pension plan.

How to apply:

Qualified applicants should submit their resume and cover letter to hr@carms.ca

If you are contacted by CaRMS for a job opportunity and require any accommodation or assistance, please inform us directly at hr@carms.ca.

The CaRMS team celebrates diversity and is committed to creating an inclusive environment for all employees. We welcome those who would contribute to the further diversification of our organization including, but not limited to: women; visible minorities; First Nations, Inuit, and Métis peoples; persons with disabilities; and persons of any sexual orientation, gender identity and/or expression.