Lead Data Scientist

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.

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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

Country:

Canada

Work hours/week:

37.5

Employment Type:

Full time

Platform:

PERSONAL & COMMERCIAL BANKING

Job Type:

Regular

Pay Type:

Salaried

Posted Date:

2024-10-04

Application Deadline:

2024-11-15

Inclusion 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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