Flinks
Senior Data Scientist
Toronto, Ontario, Canada · Senior
No sponsorship$120k-$160kDetected 43 days ago
PythonFastAPISQLBigQueryGCPAzureCloud PlatformsCI/CDDevOpsMachine LearningPyTorchData EngineeringData ScienceNLPStatisticsA/B TestingForecastingValuationResearchExperimental Design
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odds of building a lasting career here
33Unrated
Cap-exempt (no lottery)0
Sponsors this role0
Entry-level history0
PERM / green-card track0
Lottery odds (Level III)83
Fits your clock70
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About the role
- We're explicit about this because it matters: if you're looking for a pure research or notebook-only role, this isn't it.
Responsibilities
- Own ML models end to end - frame the problem, write the design/RFC, build and train the model, ship it to a served endpoint and monitor its quality in production.
- Build your model's training pipeline and package it for serving, deploying onto the shared platform Data Engineering builds and operates.
- Own model quality, not the platform - you watch drift and performance and decide when to retrain.
- Evaluate rigorously - experimental design, statistical validation, drift detection and retraining, champion-challenger evaluation and promotion.
- Partner across the org - your model outputs feed the attributes/enrichment layer, payments risk, dashboards and client integrations, you'll collaborate with Data Engineering, backend, product and QA on contracts, deployment and rollout.
- Move fast with AI-assisted development -we use it to accelerate implementation and experimentation, the highest-leverage contribution in this role comes from strong problem framing, system design, evaluation rigor and clear technical specifications.
- What You'll Work On A few of the live ML systems this role owns end to end: Transaction categorization - a hierarchical, multi-task BERT classifier running as segment based models, trained on labelled data with synthetic top-ups for rare classes.
- Model-quality and analytics tooling - the data-science team's own model-performance, PSI / drift and category-distribution monitoring for the models it owns.
- Ce que vous ferez Prendre en charge les modèles de ML de bout en bout: définition du problème, rédaction des documents de conception (RFC), développement, entraînement, déploiement et suivi en production.
Requirements
- production-grade Python and the ability to take a model to a live, monitored service yourself, on a solid data-science / ML foundation.
- must be legally authorized to work in Canada.
Nice to have
- Transaction categorization - a hierarchical, multi-task BERT classifier running as segment based models, trained on labelled data with synthetic top-ups for rare classes.
- Transaction NER parser - a multilingual token-classifier extracting entity types from raw descriptions.
- Payments risk and balance forecasting - quantile time-series forecasting feeding a risk/offer decision layer.
- The enrichment suite - income / net-income, frequency detection, plus employment-loss, life-events and pay-frequency models.
- strong production-ML fundamentals matter more than direct experience with our exact stack.
- Python is the exception:
- it's a non-negotiable (see Key Requirements).
- A modern, cloud-native ML stack with an AI-assisted development workflow.
Compensation
- For experienced and qualified hires located in Canada, of senior (IC4) level, the compensation range is between $120,000 to $160,000 CAD annually.
Benefits
- Career development, learning opportunities and growth And more We are committed to providing accommodations for persons with disabilities.
Company info
- As part of the total rewards package, Flinks offers: Health & Dental coverage as of Day 1 Flexible Paid Time Off (FTO) Remote work environment with frequent in-person gatherings and activities.
Equal opportunity
- If you require accommodation, we will work with you to meet your needs.
Visa & Work Authorization
- must be legally authorized to work in Canada.
This listing is sourced directly from Flinks's careers page and normalized into a canonical job model.