Data Scientist at RBC

About The Company

RBC, also known as the Royal Bank of Canada, is one of the largest and most reputable financial institutions globally. With a rich history spanning over a century, RBC has established itself as a leader in banking, investment, and financial services. The organization is committed to delivering innovative solutions, exceptional client experiences, and fostering a diverse and inclusive workplace. RBC prides itself on its strong corporate values, dedication to community engagement, and continuous pursuit of excellence in all its endeavors.

About The Role

The Data Scientist role at RBC offers an exciting opportunity to join the Advanced Data Insights & Integration (ADII) Team within Personal Banking. This team focuses on leveraging advanced analytics and machine learning techniques to optimize marketing strategies and enhance client engagement. As a Data Scientist, you will be instrumental in designing, developing, and deploying end-to-end marketing models that drive client acquisition and retention. Your work will involve utilizing state-of-the-art tools and frameworks to build scalable, modular solutions that support the bank's strategic goals. This role requires a combination of technical expertise, innovative thinking, and a deep understanding of marketing analytics to maintain RBC’s industry-leading position in advanced marketing techniques.

Qualifications

• Bachelor’s or Master’s degree in Statistics, Computer Science, Data Science, Economics, Operations Research, Mathematics, or a related quantitative field
• 3-5+ years of experience in data science, marketing analytics, or ML engineering with a proven track record of building and deploying production-grade analytics solutions
• Hands-on experience with open-source MMM frameworks such as Meta Robyn (R-based) or Google Meridian (Python-based)
• Deep understanding of MMM concepts including adstock, saturation, decomposition, and Bayesian inference
• Advanced proficiency in Python, including pandas, numpy, statsmodels, scikit-learn, tensorflow/pytorch, and visualization tools like plotly, matplotlib, seaborn
• Strong SQL skills with experience in complex queries, joins, and query optimization; familiarity with cloud platforms like AWS S3, Glue, SageMaker or equivalents
• Experience working with big data frameworks such as Apache Spark, Hadoop, Hive
• Proficiency with cloud and on-premises notebook environments such as Jupyter, Databricks, SageMaker
• Optimization expertise using tools like SciPy, PuLP, Pyomo, Google OR‑Tools
• Experience in building modular, scalable analytics frameworks with proficiency in Git, version control, and CI/CD processes
• Expertise in statistical and ML techniques including regression analysis, time-series modeling, Bayesian methods, causal inference, experimental design, propensity modeling, attribution, segmentation, CLV, and supervised/unsupervised learning
• Strong ability to translate business requirements into technical solutions, preferably with experience in financial services or regulated industries
  
  

Responsibilities

• Design and implement production‑grade, modular Marketing Mix Modeling (MMM) pipelines, including data collection, feature engineering, model training, inference, forecasting, optimization, monitoring, and retraining
• Utilize open-source frameworks such as Meta Robyn or Google Meridian to develop scalable solutions across multiple products and lines of business
• Prepare, parse, and integrate large volumes of structured and unstructured data, ensuring privacy preservation and unbiased estimates
• Implement data quality checks, validation rules, and anomaly detection mechanisms for incoming data streams
• Document and validate model designs and performance metrics to ensure quality, scalability, and compliance
• Develop custom optimization engines to recommend media budgets based on model outputs, constraints, and business objectives, integrating results with visualization platforms
• Research emerging technologies and methodologies to foster innovation within the team
• Work primarily within the AWS environment, leveraging services such as SageMaker, S3, and Redshift to meet business needs
• Collaborate with cross-functional teams to translate complex data insights into actionable strategies
• Maintain and improve existing analytics frameworks, ensuring robustness and reusability
  
  

Benefits

• Comprehensive Total Rewards Program including bonuses, flexible benefits, competitive salary, commissions, and stock options where applicable
• Leadership support for professional growth through coaching and development opportunities
• Opportunity to make a meaningful impact within a globally recognized organization
• Access to world-class training programs in financial services and analytics
• Flexible work arrangements promoting work/life balance
• Collaborative and inclusive work environment fostering diversity and innovation
  
  

Equal Opportunity

At RBC, we are committed to fostering an inclusive workplace that values diversity and promotes equal opportunity. We believe that a workplace with diverse perspectives enhances our ability to serve our clients effectively and drives innovation. We provide equal employment opportunities regardless of race, gender, age, religion, sexual orientation, disability, or any other characteristic protected by law.