BMO Financial Group is seeking a data scientist to drive data-informed decision-making across marketing strategy, media investment and optimization, customer engagement, and campaign performance by developing and implementing advanced analytical solutions.
Requirements
- Proficiency in statistical and analytical tools: Python, SQL, SAS
- Experience with data visualization tools: Power BI
- Experience with cloud-based data platforms (e.g., AWS, GCP, DataIku)
- Strong understanding of predictive modeling, clustering, classification, regression, causal inference, and marketing-specific modeling techniques
- Knowledge of experimentation frameworks, uplift modeling, and A/B testing
- Experience with MLOps
- Familiarity with media data sources (e.g., Kantar, Nielsen, Google Ads, Meta)
Responsibilities
- Design, develop, and implement innovative data science models to support marketing initiatives such as customer lifetime value (CLTV) prediction, customer segmentation and clustering, lookalike modeling, churn prediction, uplift modeling and experimentation frameworks, personalization and targeting algorithms, and campaign response modeling.
- Provide expert guidance on the configuration, functionality, and usability of data management, analytics, and visualization technologies.
- Support the development of strategy and roadmap for data quality, modeling, reporting, and advanced decision support tools.
- Lead and contribute to the design, implementation, and management of new analytics and reporting solutions.
- Develop and deliver regular and ad-hoc reports, dashboards, and visualizations to communicate insights clearly to diverse audiences.
- Structure and assemble multi-dimensional data sets across various granularities (e.g., customer, product, transaction, media).
- Integrate data from multiple sources to enhance analysis, streamline reporting, and improve marketing performance measurement.
Other
- Partner with marketing and cross-functional teams to understand business needs and deliver analytical solutions that drive better marketing outcomes.
- Build and maintain effective relationships with internal and external stakeholders to align analytics with business goals.
- Support strategic analytics initiatives in collaboration with cross-functional teams.
- Develop tools and training programs to enable self-serve analytics for non-technical users.
- Document and maintain operational procedures related to analytical and reporting processes.
