Junior data scientist supporting derivatives, VaR, stress testing, and regulatory risk models at Desjardins. Implementing methodologies and risk - system products in a hybrid Montréal role.
About the role
- Data Scientist building production ML, NLP, and GenAI solutions for Irth’s critical-infrastructure SaaS platform. Developing Databricks pipelines and maintainable software for damage prevention and asset integrity.
Responsibilities
- Design, prototype, and evaluate LLM/NLP solutions for business and technical needs.
- Develop text classification, entity extraction, semantic search, summarization, and other NLP/AI applications.
- Experiment with models and techniques and evaluate model quality, performance, and relevance before production.
- Explore, prepare, transform, and analyze data using Databricks.
- Develop and improve data pipelines for machine learning and AI solutions.
- Transform successful prototypes and proofs of concept into production-ready solutions.
- Develop clean, modular, maintainable, and well-tested code using object-oriented design and software engineering practices.
- Analyze, improve, consolidate, or redesign existing codebases, data pipelines, and applications.
- Improve reliability, scalability, performance, and maintainability.
- Collaborate with data engineering, application development, engineering, leadership, and stakeholders.
- Participate in technical and architectural decisions and establish improved development, testing, and deployment practices.
- Translate business needs into practical technical solutions and deliver measurable value for Irth’s SaaS products serving critical infrastructure industries.
Requirements
- 3–5 years of experience in data science, machine learning, or ML engineering, with demonstrated production-quality coding experience beyond notebooks.
- Master’s degree or equivalent professional experience in data science, machine learning, computer science, statistics, or a related field, with a strong foundation in statistics and modeling methodologies.
- Hands-on experience developing NLP and/or LLM-based solutions, including RAG, embeddings and cosine similarity, hybrid BM25/semantic search, fuzzy matching, MinHash, text classification, NER, search re-ranking, and prompt engineering.
- Strong proficiency in Python, including pandas, scikit-learn, PyTorch, and other relevant machine learning libraries.
- Strong understanding of object-oriented programming, clean code, and software design principles.
- Strong data analysis skills, including exploratory data analysis, hypothesis testing, and statistical modeling.
- Hands-on experience with Databricks or a comparable data/analytics platform.
- Understanding of the machine learning lifecycle, including training, evaluation, deployment, production monitoring, model drift, and data quality.
- Experience designing and developing REST APIs.
- Strong written and verbal communication skills; French and English proficiency explicitly required in the French qualifications.
- Nice to have: experience with large-scale unstructured text data, communications/public relations/media, vector databases, RAG frameworks, NLP fine-tuning, MLflow, TypeScript, Node.js, CI/CD, Git, and GitHub Actions.
Benefits
- Competitive Salary – A competitive compensation package based on experience and qualifications.
- Medical, Dental, and Vision Insurance – Comprehensive insurance coverage to support you and your family.
- 401(k) Plan with Company Match.
- Generous Paid Time Off (PTO).
- Company-Paid Holidays.
- Flexible Work Options – Work-from-home opportunities are available, depending on the role and business needs.
- On-Call Compensation – Additional pay for eligible on-call shifts.
- Competitive Salary — A competitive compensation package based on experience and qualifications.
- Medical, Dental, and Vision Insurance — Comprehensive insurance coverage to support you and your family.
- Retirement Plan with Employer Matching.
- Generous Paid Time Off.
- Company-Paid Holidays.
- Flexible Work Arrangements — Remote work opportunities are available depending on the role and business needs.
- On-Call Compensation — Additional pay for eligible on-call shifts.
Job title
Job type
Experience level
Salary
Degree requirement
Tech skills
Location requirements
Report this job
Found something wrong with the page? Please let us know by submitting a report below.
Evaluating data science and quantitative AI outputs for Gramian Consultancy, an IT professional services and engineering talent consultancy. Creating prompts, datasets, and feedback to improve AI models.
Data Scientist structuring medical knowledge and evaluating AI - driven educational products for Lecturio, a global medical and nursing e - learning platform. Developing statistical validation frameworks and Knowledge Graph API integrations.
Credit risk modelling data scientist developing and maintaining models for Desjardins. Guiding risk quantification, credit decisions, compliance, and practitioner - led modelling projects.
Data Scientist developing transactional fraud detection models for Desjardins’ banking and debit payments. Deploying analytics, dashboards, and mitigation strategies to protect members and clients.
Product analytics consultant delivering business insights and dashboards for Allstate Canada’s personal insurance portfolio. Supporting strategic decisions through performance analysis, reporting automation, and stakeholder recommendations.
Growth Data Scientist partnering with product, design, engineering, and marketing leaders at fintech Mercury. Shaping banking growth strategy through funnel analytics, experimentation, and prioritized recommendations.
Principal Data Scientist leading causal marketing measurement for Upstart’s AI lending marketplace. Guiding attribution, experimentation, and budget allocation across growth channels.
Senior actuarial advisor commercializing predictive modeling and advanced analytics for Desjardins insurance pricing. Deploying innovative capabilities across Personal and Commercial Insurance.
Senior Data Scientist defining rigorous evaluation systems for AI models and agents. Improving quality and safe rollout at Alpaca, a global brokerage - infrastructure company.