Senior Data Scientist

You will own machine-learning models end to end, from framing the problem and writing the design/RFC through building the training pipeline, deploying to a live endpoint, and monitoring model quality in production. You will build and ship your own models on a shared platform operated by Data Engineering, watch drift and performance, and decide when to retrain. You will evaluate rigorously using experimental design, statistical validation, drift detection, and champion-challenger promotion. You will work on live ML systems such as transaction categorization with a multi-task BERT classifier, reversal detection, a multilingual transaction NER parser, payments risk and balance forecasting, and an enrichment suite covering income, frequency, and life-event models. You will collaborate with Data Engineering, backend, product, and QA on contracts, deployment, and rollout, and use AI-assisted development to accelerate implementation and experimentation.

Responsibilities

• Own ML models end to end, from problem framing and design/RFC through training, deployment, and production monitoring
• Build model training pipelines and package models for serving on the shared platform
• Monitor model drift and performance and decide when to retrain
• Design rigorous evaluations including experimental design, statistical validation, drift detection, and champion-challenger promotion
• Collaborate with Data Engineering, backend, product, and QA on contracts, deployment, and rollout
• Connect model improvements to business outcomes such as risk reduction, enrichment accuracy, customer adoption, and revenue
• Use AI-assisted development to accelerate implementation and experimentation

Requirements

• 6-8 years building and shipping machine-learning models, including taking models to production
• Bachelor's degree in a quantitative field (Computer Science, Statistics, Applied Mathematics, or related); Master's or PhD is an asset
• Production-grade Python skills
• Ability to take a model to a live, monitored service independently
• Solid data science and ML foundation
• Legally authorized to work in Canada

Benefits

• Health & Dental coverage as of Day 1
• Flexible Paid Time Off (FTO)
• Remote work environment with frequent in-person gatherings and activities