What’s in it for you as an employee of QFG?

• Health & wellbeing resources and programs

• Paid vacation, personal, and sick days for work-life balance

• Competitive compensation and benefits packages

• Work-life balance in a hybrid environment with at least 3 days in office

• Career growth and development opportunities

• Opportunities to contribute to community causes

• Work with diverse team members in an inclusive and collaborative environment

We’re looking for our next Director, Data Science & AI Enablement. Could It Be You?

The Data Science & AI Enablement group is critical to delivering QFG’s bold vision for convenient and hyper-personalized financial services. This vision is realized through a comprehensive Artificial Intelligence (AI) strategy that spans the entire organization.

The Director, Data Science & AI Enablement will lead the implementation and adoption of this strategy across four interconnected segments:

• AI for Everyone: Making day-to-day work easier and more efficient.

• AI for Citizen Innovators: Empowering employees to build custom automations.

• AI for Builders: Integrating AI to accelerate and improve engineering craft.

• AI for Customers: Building proprietary AI products that drive competitive advantage.

This role partners across all areas to build a data-driven and engineering organization with the intelligence necessary to enable these hyper-personalized experiences for our customers and enhance internal operations.

The Director, Data Science & AI Enablement is a key leadership role responsible for defining the strategic direction and leading the implementation of QFG’s comprehensive AI strategy. This leader commands the Data Science and AI Enablement team, owning the operational availability, research, and governance of all AI and LLM models. The role drives cross-organizational enablement, focusing on internal productivity, process innovation, and the creation of proprietary customer products. This Director also serves as the thought leader, maintaining the AI Center of Excellence (COE) and AI Council. This requires a strong blend of technical acumen, strategic thinking, and the ability to influence cross-functional teams to build a cutting-edge, data-driven financial services platform.

Need more details? Keep reading…

In this role, responsibilities include but are not limited to:

• Define the overarching AI strategy and ensure its successful implementation across the organization's four strategic segments (Employees, Citizen Innovators, Builders, and Customers).

• Lead the Data Science and AI Enablement team, supporting the operational availability and reliability for all deployed AI and LLM models.

• Direct the entire model lifecycle, including model selection, fine-tuning, prompt engineering research, RAG design, model benchmarking, and ongoing evaluation.

• Serve as the principal thought leader, maintaining and leading the AI Center of Excellence (COE) and the AI Council. Collaborate actively with Enterprise Architecture and Cybersecurity to ensure all models and guardrails meet corporate standards and compliance requirements.

• Own the definition and delivery of performance metrics for the AI portfolio, ensuring model accuracy and direct positive impact on key business metrics.

• Collaborate with the entities and enterprise teams to identify AI related opportunities and provide appropriate support and leadership to effectively meet established outcomes.

• Drive comprehensive AI enablement by embedding the AI & Data Science team into different business functions to accelerate their AI journey.

• Support the various entities/LOBs and business leaders in providing expertise and guidance on the AI specific discipline, ensuring practices are aligned, resourced and working effectively to meet strategic objectives

• Work with Product Managers/Product Owners to develop, execute, and test different hypotheses that have a significant impact on customer experiences

• Work closely with Business and Technology leadership to find opportunities for innovation and serve as an evangelist for data science and AI

• Partner with cross-functional teams including engineering, UX/UI, sales, marketing, customer support, operations etc to identify pain-points and develop analytical solutions

• Develop powerful business insights from diverse data-sets including social, marketing, transactions data using advanced machine learning techniques (NLU/NLP, DeepLearning)

• Build models and algorithms that help power products and services that lead to more intelligent and effective engagement with our customers

• Collaborate with Engineering teams to help implement machine learning algorithms and “productionize" data science solutions

• Provide insight into leading analytics practices that help management and stakeholders to evaluate trends, tools and vendor offerings in this space

• Share learnings through internal training and workshops and develop the Data Science and AI practice through thought leadership and staying current on developments in the area of data sciences

• Translate and communicate complex algorithms to non-technical individuals. Model explainability is key to gain support from various teams within the organization and also important from a regulatory compliance point of view

• Excellent interpersonal communication and presentation skills for all levels of the organization including senior executive level

• Leadership and management skills that result in high-performing teams

• Ability to influence and drive change, combined with the drive to deliver results

• Makes decisions and recommendations clearly linked to the organization’s strategy

• Communicates ideas or positions in a persuasive manner that builds support, agreement or commitment

• Excels at sharing knowledge and propelling data-driven and engineering culture

PEOPLE MANAGEMENT

• Manage the team of people who comprise the group

• Align technical teams and individual goals to the organization’s strategic goals.

• Forecast resourcing needs based on strategic goals, to ensure those are met.

• Make sure that team skill sets and knowledge are well distributed, creating as much learning and growth opportunities as possible for individual contributors.

• Be resourceful and elaborate alternative plans to address hiring needs if there are challenges fulfilling them.

• Be an advocate for the teams, removing efficiency blockers, and helping them get the tools and processes they need to be high performing, especially when this requires presenting a case to obtain support from the organization. Ensure this is done in a timely fashion, as this role is ultimately accountable for the team’s results.

• Provide mentoring to team members to assist them in reaching their career goals.

• Address team member performance issues in a timely manner, before it impacts deliverables significantly.

TECHNOLOGY STRATEGY

• The incumbent will align with the Senior Technology Leadership team on strategic imperatives and will help define the resources, org structures and cultural changes necessary to support the technology strategy.

OTHER LEADERSHIP RESPONSIBILITIES

• Be an active voice in defining and implementing best practices, standards and procedures including quality and delivery methodologies.

• Make sure that code written within scoped teams is reviewed and tested appropriately.

• Assumes responsibility for the ongoing architecture compliance of the scoped platforms.

• Conducts research and proof of concepts, ensuring the value is documented and socialized.

• Assist teams with sharing knowledge and lessons learned with others in the organization.

• Apply significant knowledge of the technology industry trends to help Questrade to improve and build innovative products.

So are YOU our next Director, Data Science & AI Enablement? You are if you…

• Deep knowledge of math, statistics, probability and algorithms

• Comprehensive understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc.

• Experience of using Visualization tools like PowerBI or similar

• Familiarity with using popular machine learning frameworks and libraries like PyTorch,Keras, SciKit-learn, sparkML etc

• Large experience manipulating and analyzing data sets through query languages such as SQL and through programming languages like Python, Scala, etc.

• Hands on Programming/Scripting experience in one of Python, Scala, R etc.

• Knowledge of Cloud computing platforms like Google cloud (preferred), AWS, Azure etc

• Financial domain knowledge especially Brokerage and Retail Banking

• Knowledgeable in financial analysis, strategy formation and business case development

• Masters or PhD in Mathematics, Statistics, Actuarial Sciences or related fields
  
  

Sounds like you? Click below to apply!

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