Data Scientist, Staff

About The Company
RBC (Royal Bank of Canada) is one of the largest and most reputable financial institutions in Canada and globally, renowned for its commitment to innovation, customer service, and community support. With a rich history spanning over a century, RBC offers a wide range of financial services including personal banking, commercial banking, wealth management, and investment banking. The organization prides itself on fostering a diverse and inclusive workplace culture that encourages professional growth, collaboration, and continuous learning. RBC leverages cutting-edge technology and data-driven strategies to maintain its industry leadership and deliver exceptional value to clients and stakeholders worldwide.

About The Role
The Advanced Data Insights & Integration (ADII) Team within Personal Banking at RBC is seeking a highly skilled and innovative Data Scientist to join our Marketing Optimization & Planning pillar. This role offers an exciting opportunity to design, develop, and deploy sophisticated machine learning models and applications that enhance our marketing strategies. As a key member of the team, you will work on end-to-end marketing analytics solutions, including data collection, feature engineering, model training, inference, and ongoing model maintenance. Your work will directly influence client acquisition efforts and help maintain RBC's position as an industry leader in advanced marketing techniques. The role involves collaborating with cross-functional teams, leveraging cloud platforms such as AWS, and utilizing state-of-the-art tools and frameworks to drive data-driven decision-making and optimize marketing spend.

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: pandas, numpy, statsmodels, scikit-learn, tensorflow/pytorch, and visualization tools like plotly, matplotlib, seaborn
• Strong SQL skills: complex queries, joins, query optimization, and experience with cloud platforms (AWS S3, Glue, SageMaker) and big data frameworks (Apache Spark, Hadoop, Hive)
• Experience working with cloud and on-premises environments such as Jupyter, Databricks, or SageMaker
• Expertise in optimization techniques: SciPy, PuLP, Pyomo, Google OR-Tools, and the ability to formulate business problems as mathematical optimization problems
• Proficiency in building modular, scalable analytics frameworks, version control (Git), and CI/CD pipelines for models
• Strong knowledge of statistical and ML techniques: regression, time-series modeling, Bayesian methods, causal inference, experimental design, propensity modeling, attribution, segmentation, CLV, and behavior analysis
• Excellent ability to translate business requirements into technical solutions, with experience in highly regulated industries preferred

Responsibilities

• Design, develop, and productionize modular, scalable Marketing Mix Modeling (MMM) pipelines, including data collection, feature engineering, model training, inference, and maintenance
• Implement data quality checks, validation rules, and anomaly detection to ensure data integrity and model accuracy
• Document and validate model design and performance, ensuring robustness and scalability across multiple products and lines of business
• Create custom optimization engines to recommend media budgets, considering model outputs and spend constraints
• Integrate models and insights with visualization platforms to support marketing decision-making
• Research and evaluate new capabilities, tools, and technologies to foster innovation in marketing analytics
• Collaborate within AWS environment, utilizing services such as SageMaker, S3, and Redshift to meet business objectives
• Work closely with cross-functional teams including marketing, data engineering, and product management to deliver impactful solutions

Benefits

• Comprehensive Total Rewards Program including bonuses, flexible benefits, and competitive compensation packages
• Opportunities for professional development through world-class training programs in financial services
• Supportive leadership that encourages growth, coaching, and career advancement
• Flexible work arrangements to promote work/life balance
• Participation in innovative projects that make a lasting impact on clients and communities
• Access to cutting-edge technology and tools in a collaborative environment

Equal Opportunity

At RBC, we are committed to fostering an inclusive workplace that values diversity and promotes equal opportunity for all employees. We believe that a workplace with diverse perspectives enhances innovation, collaboration, and overall success. We strive to create a supportive environment where everyone feels respected, valued, and empowered to perform at their best. RBC is dedicated to policies and programs that promote equity, belonging, and professional growth, ensuring that all individuals have the opportunity to thrive regardless of background or identity.