Lead Data Scientist

What is the Opportunity?

The Next Best Action (NBA) Machine Learning team of Personal and Commercial Banking is looking for a passionate and innovative Senior Data Scientist. As a Data Scientist you will problem solve, analyze, design, implement and monitor machine learning applications using state of the art tools and algorithms. We are looking to maintain our position as the industry leader in deepening client relationships and engagement through the implementation of NBA Strategy. 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? 

• Interact with RBC internal partners and lines of businesses to help them frame their use cases and define success metrics (Key Performance Indicators). 

• Prepare, parse and integrate large and varied structured and unstructured data 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. 

• Contribute to the migration of existing and new models to a Cloud environment as well as expansion of Marketing Actions and Machine Learning Models of the NBA System 

• Validate the offline performance of models and work in a Continuous Integration manner. 

• Deploy solutions for end users and help drive change in a Continuous Deployment manner. 

• 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 

• Masters in Computer Science, Computer Engineering or similar field.  

• 3+ years of hands-on experience or similar post-grad work in applying Machine Learning to Customer Marketing. 

• Experience with machine learning development lifecycle and deep learning methods such as Transformers, GANs, DQN, VAE, SHAP, Counterfactuals and Adversarial examples etc. 

• Experience with Python and common machine learning/deep learning libraries Tensorflow, PyTorch, scikit-learn, huggingface etc. 

• Knowledge of big data ecosystem Hadoop/Spark. 

• Knowledge of public cloud (Azure, AWS, GCP, OpenShift) platforms and development of applications in cloud/hybrid environments 

• Familiarity with collaborative software development tools (git, issue tracking) and *nix environments 

• Strong interpersonal and communication skills (both written and verbal) across peers and senior leaders  

Nice to have 

• Strong knowledge machine learning application design. Experience deploying models into productions with MLOps (MlFlow, KubeFlow etc). 

• Experience in running A/B 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 

• Experience in developing attrition models with proven success.  

• Publications in machine learning and artificial intelligence. 

• Passion for ethical AI and experience in algorithm transparency and interpretability.  

• Knowledge of banking data.  

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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