Senior Data Scientist (Applied ML)

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Scientist (Applied ML) based in Canada. We are looking for an experienced Senior Data Scientist to build and scale advanced machine learning solutions that drive business growth and improve customer experiences. In this hands-on role, you will lead the development of production-ready predictive models, recommendation engines, and personalization systems. You will work on high-impact applications such as customer lifetime value prediction, lead scoring, conversion optimization, and personalized financial product recommendations. Collaborating with Data Engineering, Product, Marketing, and Analytics teams, you will transform complex business challenges into scalable, data-driven solutions. As a foundational member of a growing team, you will help establish machine learning standards, technical best practices, and scalable infrastructure. This is an opportunity to shape the future of applied AI and machine learning within a collaborative, remote-first environment while delivering measurable business impact. Accountabilities - Lead the end-to-end development, deployment, and optimization of advanced machine learning models focused on customer lifetime value (LTV), conversion propensity, lead quality, and revenue optimization. - Translate predictive model outputs into actionable business insights that improve marketing investment decisions, customer acquisition efficiency, and long-term profitability. - Design, develop, and implement recommendation and ranking systems that match consumers with relevant financial products based on their individual needs, behaviors, and likelihood to engage or convert. - Explore and apply advanced machine learning approaches, including propensity modeling, learning-to-rank, and next-best-product recommendation systems, to improve customer engagement and cross-selling opportunities.

- Collaborate with Product and Marketing teams to integrate predictive intelligence into consumer-facing experiences, personalized communications, and customer acquisition strategies. - Leverage Databricks and MLflow to build, train, deploy, monitor, and manage production-grade machine learning models and workflows at scale. - Establish and maintain robust data science practices, including experiment tracking, model versioning, feature engineering, automated training pipelines, monitoring, and reproducibility. - Define and implement technical standards for model performance, reliability, retraining, and production readiness, including monitoring for data drift and model degradation. - Design and conduct experiments to measure the incremental business impact of deployed models and continuously improve their effectiveness. - Develop scalable batch and real-time inference solutions, balancing latency, reliability, performance, and business requirements. - Take ownership of complex technical initiatives, from initial problem definition and solution design through deployment, monitoring, and business impact measurement. - Act as a technical leader within the Data Science function by mentoring fellow practitioners, influencing architectural decisions, and strengthening machine learning engineering and modeling standards. - Partner with cross-functional stakeholders to ensure machine learning solutions address real business needs and deliver measurable improvements in revenue, conversion, customer lifetime value, and marketing efficiency. Requirements - At least 5 years of professional experience in Data Science, Applied Machine Learning, or a related discipline, with a proven track record of developing and deploying machine learning solutions that generate measurable business results. - Extensive, hands-on experience with Databricks , including building and managing production machine learning workflows using MLflow and the broader Databricks ML ecosystem.