Senior Data Scientist – Applied ML

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

📋 Description

• Oversee the complete development lifecycle of machine learning models focusing on customer lifetime value, conversion propensity, lead quality, and revenue enhancement.

• Convert model predictions into actionable insights that enhance marketing investment strategies, customer acquisition efficiency, and sustainable profitability.

• Create recommendation and ranking models to provide tailored financial product suggestions.

• Execute propensity modeling, learning-to-rank methodologies, and next-best-product recommendations.

• Embed predictive intelligence within consumer experiences and personalized communications in collaboration with Product and Marketing teams.

• Leverage Databricks and MLflow for the development, training, deployment, monitoring, and management of models at scale.

• Set up systems for experiment tracking, model versioning, feature engineering, automated training pipelines, model monitoring, and reproducibility practices.

• Define benchmarks for model performance, reliability, retraining, and readiness for production.

• Track data drift and monitor model performance degradation.

• Design and assess experiments that quantify incremental business impact.

• Guide practitioners, influence architectural choices, and enhance engineering and modeling standards.

• Collaborate with Data Engineering, Product, Marketing, and Analytics to translate business challenges into scalable machine learning solutions.

⛳️ Requirements

• A minimum of 5 years of professional experience in Data Science, Applied Machine Learning, or a closely related field.

• Practical experience with Databricks, building and managing production-level machine learning workflows utilizing MLflow and the Databricks ML ecosystem; experience with similar platforms is not considered equivalent.

• Advanced skills in Python and SQL.

• Significant experience with libraries such as scikit-learn, XGBoost, LightGBM, PyTorch, or TensorFlow.

• Deep understanding of supervised learning, predictive modeling, classification, regression, ranking, and evaluation techniques for models.

• Experience in designing scalable batch and/or real-time inference systems.

• Knowledge of latency, reliability, and performance trade-offs.

• Strong foundation in software engineering principles, including version control, testing, modular code design, and CI/CD best practices for machine learning.

• Capacity to independently lead complex and ambiguous technical projects from problem identification through to deployment and measurement of business impact.

• Strong business insight to connect technical solutions with measurable results.

• Exceptional communication and collaboration abilities; experience in influencing technical direction and engaging with senior stakeholders and cross-functional teams.

• A Bachelor's or advanced degree in Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field, or equivalent hands-on experience.

• Must reside anywhere in Canada excluding Quebec.

• Must possess authorization to work in Canada.

🏝️ Benefits

• Monthly Healthcare Stipend.

• Rejuvenation Policy – Vacation Time Off + official public holidays as per your province.

• Paid sabbatical.

• Monthly Wellness Stipend.

• Wifi Stipend.

• Cell Phone Stipend.

• Equipment stipend for working from home.

• Employee Resource Groups.

• Participation in hackathons and team events.

• Company-wide events.

• RRSP with a 4% match, eligible one month post-hire.

• Financial wellness guidance and unlimited access to a Certified Financial Planner (CFP) through Northstar.