Job Summary
Job Description
What is the Opportunity?
The Personal Banking & Commercial Banking Data Strategy team is looking for a passionate and innovative Lead Data Scientist within our advanced marketing pillar.
As a Data Scientist you will problem solve, analyze, design, implement and monitor machine learning models and applications using state of the art tools and algorithms.
We are looking to maintain our position as an industry leader in advanced digital marketing techniques (Multi-touch Attribution, Media Mix Modeling and Testing Strategies) and continue to drive strong client acquisition results.
To achieve these goals, we leverage diverse data sources and a suite of domain specific machine learning models that power our client communications.
What will you do?
Design, build, validate and deploy advanced marketing models related to programmatic advertising platforms, product recommenders, propensity models and prospect personalization models to maximize client acquisition and efficiency.
Partner with RBC internal partners and lines of businesses (Digital Marketing, Programmatic Media) to help them frame use cases and define success metrics (Key Performance Indicators).
Work primarily within our AWS environment (SageMaker, S3, Redshift) to accomplish business goals
Prepare, parse and integrate large and varied structured and unstructured data on AWS and on prem for model training and scoring while preserving privacy and unbiased estimates.
Develop state of the art machine learning models end-to end, including feature engineering, model training, model inference, model production, model monitoring and model maintenance.
Document and Validate model design and performance to ensure quality and scalability of all models
Monitor model performance and business success metrics over time.
Be responsible for researching new capabilities and technologies to drive innovation
What do you need to succeed?
Must-have
Master's degree in Statistics, Economics, Marketing (Quantitative Workstream) Mathematics, or related quantitative field
3+ years experience in marketing science / data science in digital marketing, sales, eCommerce, or related field
Strong foundation in statistics, probability, and machine learning (including deep learning), especially in areas like : Causal inference, regression analysis, hypothesis testing, Bayesian inference, time series forecasting, propensity modelling, attrition modelling, attribution, segmentation, CLV, and behaviour analysis,
Strong programming skills in python (preferred) or R, including relevant statistical, machine learning, and deep learning libraries (pandas, numpy, stats models, scikit-learn, tensorflow / pytorch, etc.)
Good foundations in SQL, big data frameworks (Apache Spark, Hadoop, Hive, etc.), and AWS Cloud (SageMaker, S3, Redshift) or Azure / GCP equivalents
Able to clearly convey technical concepts and results to both technical and non-technical audiences, including senior leadership
Nice to have
Strong knowledge machine learning application design. Experience deploying models into productions with MLOps.
Experience with on device learning and modelling.
Experience in running A / B testing experiments in production. Experience with relational databases. Domain specific knowledge of marketing campaigns.
Experience in financial services industry with broad understanding of marketing, product management, sales, finance, pricing and risk management is preferred
Publications in machine learning and artificial intelligence.
Passion for ethical AI and experience in algorithm transparency and interpretability.
What’s in it for you?
We thrive on the challenge to be our best, progressive thinking to keep growing, and working together to deliver trusted advice to help our clients thrive and communities prosper.
We care about each other, reaching our potential, making a difference to our communities, and achieving success that is mutual.
A comprehensive Total Rewards Program including bonuses and flexible benefits, competitive compensation, commissions, and stock where applicable
Leaders who support your development through coaching and managing opportunities
Ability to make a difference and lasting impact
Work in a dynamic, collaborative, progressive, and high-performing team
A world-class training program in financial services
Opportunities to do challenging work, to take on progressively greater accountabilities and to building close relationships with clients
Access to a variety of job opportunities across business and geographies.
LI Hybrid
LI-Post
LI-PK
TECHPJ
Job Skills
Actuarial Modeling, Big Data Management, Commercial Acumen, Data Mining, Data Science, Decision Making, Machine Learning, Natural Language Processing (NLP), Predictive Analytics, Python (Programming Language)
Additional Job Details
Address :
RBC WATERPARK PLACE, 88 QUEENS QUAY W : TORONTO
City : TORONTO
TORONTO
Country : Canada
Canada
Work hours / week : 37.5
37.5
Employment Type : Full time
Full time
Platform :
PERSONAL & COMMERCIAL BANKING
Job Type : Regular
Regular
Pay Type : Salaried
Salaried
Posted Date : 2024-10-04
2024-10-04
Application Deadline :
2024-11-15
I nclusion and Equal Opportunity Employment
At RBC, we embrace diversity and inclusion for innovation and growth. We are committed to building inclusive teams and an equitable workplace for our employees to bring their true selves to work.
We are taking actions to tackle issues of inequity and systemic bias to support our diverse talent, clients and communities.
We also strive to provide an accessible candidate experience for our prospective employees with different abilities. Please let us know if you need any accommodations during the recruitment process.
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