Senior Data Scientist, Sales Practices & Conduct

Job description

Come Work with Us!

At RBC, our culture is deeply supportive and rich in opportunity and reward. You will help our clients thrive and our communities prosper, empowered by a spirit of shared purpose.

Whether you’re helping clients find new opportunities, developing new technology, or providing expert advice to internal partners, you will be doing work that matters in the world, in an environment built on teamwork, service, responsibility, diversity, and integrity.

Job Title

Senior Data Scientist, Sales Practices & Conduct

Job Description

What is the Opportunity?

The Retail Banking industry is changing rapidly with digitization of products, services, and channels, emerging non-traditional competitors, changing client demographics, preferences, and choices, and heightened regulatory attention on sales practices within retail banking sector across the globe. This role will play a critical role in designing and delivering advanced analytics aimed at mining insights from advisors' activities, sales results, client information, etc. to identify behaviors and sales practices that are not aligned with the target client experience or the RBC code of conduct. Collaborate with a diverse set of colleagues from across the enterprise (within Canadian Banking, Operations, T&O, HR, Compliance, Group Risk, etc.) and contribute to world class analytical tools that will help ensure RBC has strong and consistent sales practices in place.

What will you do?

  • Interact with RBC internal partners and lines of businesses to help frame use cases and business objectives that can benefit from analytical solutions.
  • Build on the knowledge of subject matter experts (within Retail Banking and across the enterprise) to analyze structured and unstructured data (e.g. advisor activities including client interactions, sales activities and outcomes, banking transactions etc.) and identify patterns consistent with poor/strong sales practices.
  • Apply scripting/programming skills to assemble various types of source data (unstructured, semi-structured, structured) into well-prepared datasets with multiple levels of granularities (e.g. demographics, client segments, employee role groups)
  • Develops analytical solutions by applying suitable statistical * machine learning techniques (e.g. A/B testing, prototype solutions, mathematical models, algorithms, machine learning, deep learning, artificial intelligence) to test, verify and refine hypothesis.
  • Baseline behavior across the retail banking network and identify anomalous activities.
  • Enable Retail Banking to continue to expand its proactive approach to monitoring advisor practices, advice and service delivery, client experience.
  • Participate in Proof of Concept projects to build strong linkages and predictive analytics across client experience and feedback data, advisor activities and outcomes, client demographics, etc.
  • Participate in the creation of detailed plans and accurate estimates toward the development, testing and implementation of proactive advisor practices monitoring capabilities.
  • Contribute to the successful completion of projects by identifying risks and developing/ recommending mitigation strategies.
  • Refine and iterate on existing machine learning algorithms/models based on feedback from case reviews and or changes in macro environments, regulatory requirements etc.
  • Structure loosely defined and complex business problems; determines new experimentation methods and statistical techniques to design solutions.
  • Acts as a leading subject matter expert for internal/external stakeholders.

What do you need to succeed?

Required Qualifications:

  • 5+ years of relevant experience in related field of study or an equivalent combination of experience and similar post-grad work in Machine Learning.
  • Advanced degree (Masters, Ph. D preferred) in Computer Science, Engineering, Mathematics, Statistics or other quantitative disciplines.
  • Proven track record of solving ambiguous and highly complex problems using data and machine learning.
  • Experience with machine learning development lifecycle and deep learning methods such as Transformers, GANs, DQN, VAE, SHAP, Counterfactuals and Adversarial examples etc.
  • Expert working knowledge in standard Python libraries such as pandas, numpy and matlpotlib and with standard ML Python libraries such as scikit-learn, TensorFlow or PyTorch.
  • Familiarity with data visualization tools and techniques like D3, R, Qlik, Tableau, PowerBI
  • Familiarity with a Linux environment and shell scripting.
  • Expert technical documentation skills.
  • Strong interpersonal and communication skills (both written and verbal) across peers and senior leaders.
  • Ability to work collaborative with cross-function teams and business units.

Suggested Qualifications:

  • Related experience in a role focused on risk analysis or predictive analytics.
  • Strong knowledge and experience with machine learning application design.
  • Experience deploying models into productions with MLOps (MlFlow, KubeFlow etc.).
  • Experience working with ML Cloud platforms (AWS, Azure).
  • Knowledge of big data ecosystem Hadoop/Spark.
  • Experience in running A/B experiments in production. Experience with relational databases.
  • Publications in machine learning and artificial intelligence.
  • Passion for ethical AI and experience in algorithm transparency and interpretability.

Job Summary


TORONTO, Ontario, Canada





Work hours/week:


Employment Type:

Full time


Personal and Commercial Banking

Job Type:


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Posted Date:


Application Deadline:


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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