Senior Data Scientist

This is a fully remote position, open to applicants in Canada.

📋 Description

• Take ownership of machine learning models from start to finish - define the problem, create the design/RFC, develop and train the model, deploy it to a serving endpoint, and monitor its performance in production.

• Construct the training pipeline for your model and prepare it for deployment on the shared platform managed by Data Engineering.

• Ensure model quality independently from the platform - you will monitor for drift and performance, determining the right time for retraining.

• Conduct thorough evaluations - focusing on experimental design, statistical validation, drift detection, retraining, and champion-challenger evaluations for promotion.

• Collaborate across the organization - your model outputs will contribute to the attributes/enrichment layer, payments risk, dashboards, and client integrations, necessitating collaboration with Data Engineering, backend, product, and QA teams on contracts, deployment, and rollout.

• Accelerate development with AI-assisted tools - we leverage this technology for quicker implementation and experimentation, with the most significant impact in this role arising from effective problem framing, system design, rigorous evaluation, and precise technical specifications.

⛳️ Requirements

• Experience: 6-8 years of expertise in developing and deploying machine learning models, including the end-to-end process of bringing models to production (from training pipeline to served endpoint to monitoring).

• Education: A Bachelor's degree in a quantitative discipline (such as Computer Science, Statistics, Applied Mathematics, or a related field) is required; a Master's or PhD is a plus but not mandatory.

• Non-negotiables: Proficiency in production-grade Python and the capability to independently deploy a model to a live, monitored service, grounded in a solid data science/ML foundation.

🏝️ Benefits

• Health & Dental coverage starting on Day 1

• Flexible Paid Time Off (FTO)

• Remote work environment complemented by regular in-person gatherings and activities.

• Opportunities for career development, learning, and growth

• And more