Managing Director, Marketing Analytics & Data Science
Bank of Montreal
Full-time
On-site
Toronto, Ontario, Canada
📌 Core Information
- Job Title: Managing Director, Marketing Analytics & Data Science
- Company: Bank of Montreal (BMO)
- Location: Toronto, Ontario, Canada
- Job Type: Regular, Full-Time
- Category: Data Analytics & Reporting
- Date Posted: April 15, 2025
- Experience Level: 10+ years
- Remote Status: On-site
🚀 Job Overview
Key aspects of this role include:
- Developing and leading the Marketing Data Science and Analytics strategy
- Collaborating with stakeholders to support strategic objectives
- Executing initiatives that develop data-driven insights
- Leveraging advanced analytics, AI, and machine learning to drive marketing strategy and effectiveness
- Managing a high-performing team of 20 digital marketing and analytics experts
ASSUMPTION: This role requires a strategic mindset, strong leadership skills, and deep expertise in data science, analytics, and marketing technology.
📋 Key Responsibilities
- Strategic Leadership: Develop and implement the Marketing Data Science and Analytics strategy, aligning it with business objectives and common capabilities.
- Stakeholder Management: Partner with CMOs, MCSI, CDAO, operational group/service leaders, and LOB DnA teams to understand their strategic objectives and provide trusted advisory services.
- Data-Driven Insights: Execute initiatives that develop data-driven insights on valuable opportunities with marketing and business partners.
- Model Development & Testing: Develop and test model-based proof of concepts and prototypes to assess feasibility and value-creation potential.
- Advanced Analytics: Leverage advanced analytics/AI to support marketing strategy, drive acquisition, develop customer insights, and enhance marketing effectiveness.
- Team Leadership: Lead, mentor, and develop the Data Science and Analytics Practice across multiple geographies, fostering a high-performance culture.
- Talent Acquisition & Development: Partner with Talent Acquisition to recruit, evaluate, hire talent, and invest in the talent within the organization.
ASSUMPTION: This role involves a mix of strategic planning, hands-on data science work, team leadership, and stakeholder management.
🎯 Required Qualifications
- Education: Bachelor's degree in Management Information Systems, Computer Science, Computer Engineering, or a related field. Advanced degree (e.g., MS, PhD) in a related field (e.g., Stats, Computer Science/Engineering) is preferred.
- Experience: Minimum 10 years of progressive work experience in Marketing, Computer Science, or IT, including technical leadership, project management, and management responsibilities. 5+ years of hands-on data science work experience and 5+ years of managing a data science team.
- Required Skills:
- Comprehensive practical and theoretical knowledge in Marketing Technology platforms
- Extensive hands-on leadership of Advanced Analytics teams utilizing coding languages such as SQL, SAS, Python, R, and Unix
- Experience with Salesforce tools (Marketing Cloud, Ad Studio, Interaction Studio), Marketing Automation tools (Persado, Marketo), and Analytics platforms (Google Analytics, Adobe Analytics)
- Familiarity with Marketing measurement and attribution solutions (Marketing Mix Modeling, Multi-Touch Attribution, Unified Measurement)
- Experience with supervised and unsupervised learning algorithms and their application to large data sets
- Relevant data engineering experience to architect/prototype solutions (e.g., ETL, apps, etc.)
- Experience with statistical programming languages/packages (Python, R, SAS, Scipy, etc.)
- Comfort working with the AWS-EMR and Hadoop ecosystems (Spark, MapReduce, Hive, etc.)
- Ability to partner cross-domain to solve problems and drive to recommendations
- Preferred Skills:
- Experience working in a fluid/start-up environment and with external clients
- Experience with Google Marketing and deployment of capabilities (value-based bidding models, building reporting that combines marketing campaign data with business data, Google’s next-generation AI and machine learning innovations supporting digital targeting and cyber controls)
ASSUMPTION: This role requires a well-rounded data science and analytics professional with strong leadership skills and a deep understanding of marketing technology platforms.
💰 Compensation & Benefits
- Salary Range: $190,000 - $215,000 CAD per year (target base salary range)
- Benefits:
- Health Insurance
- Tuition Reimbursement
- Accident Insurance
- Life Insurance
- Retirement Savings Plans
- Working Hours: Full-time, 40 hours per week
ASSUMPTION: The salary range provided is a target base salary range and may include a commission structure. Total compensation may include performance-based incentives, discretionary bonuses, and other perks and rewards.
📌 Applicant Insights
🔍 Company Context
- Industry: Financial Services
- Company Size: 10,001+ employees
- Founded: 1817 (as the Bank of Upper Canada)
- Company Description: BMO is a Canadian multinational investment bank and financial services company. It operates as a personal banking, commercial banking, and wealth management business with domestic operations in Canada and the United States.
- Company Specialties: Personal Banking, Commercial Banking, Wealth Management, Capital Markets, and Asset Management
📊 Role Analysis
- Career Level: Executive/Director level role, reporting directly to the Chief Marketing & Customer Experience Officer (CMCO)
- Reporting Structure: Leads a team of 20 digital marketing and analytics experts, with no direct reports mentioned
- Work Arrangement: On-site, full-time role, with no mention of hybrid or remote work arrangements
- Growth Opportunities: Potential growth opportunities include expanding the team, taking on additional responsibilities, or moving into a more senior leadership role within the organization
ASSUMPTION: This role offers significant growth opportunities for the right candidate, given the size and scope of the team and the strategic nature of the position.
🌍 Location & Work Environment
- Office Type: On-site, with no mention of remote or hybrid work arrangements
- Office Location(s): 33 Dundas Street West, Toronto, Ontario, Canada
- Geographic Context: Toronto is the capital city of the province of Ontario, with a population of approximately 2.9 million people. It is the largest city in Canada by population.
- Work Schedule: Full-time, 40 hours per week, with no mention of flexible hours or job sharing arrangements
ASSUMPTION: The on-site work arrangement may change in the future, given the company's size and the nature of the role.
💼 Interview & Application Insights
- Typical Process: The typical interview process for this role may include phone or video screens, followed by on-site interviews with relevant stakeholders, such as the hiring manager, team members, and other senior leaders within the organization.
- Key Assessment Areas: Technical skills (data science, analytics, and marketing technology), leadership skills, strategic thinking, and cultural fit
- Application Tips:
- Tailor your resume and cover letter to highlight your relevant experience and skills for this role
- Prepare for behavioral interview questions that focus on your leadership, problem-solving, and strategic thinking skills
- Research the company and the role to demonstrate your enthusiasm and understanding of the organization's mission and values
🛠️ Tools & Technologies
- AWS-EMR and Hadoop ecosystems (Spark, MapReduce, Hive, etc.)
- Statistical programming languages/packages (Python, R, SAS, Scipy, etc.)
- Marketing Technology platforms (Salesforce, Marketo, Google Analytics, Adobe Analytics)
- Data engineering tools and frameworks (ETL, ETL tools, data warehousing, data integration)
👔 Cultural Fit Considerations
- Company Values: BMO's values include integrity, humility, accountability, agility, and collaboration. The company seeks employees who embody these values and are committed to driving positive change for customers, communities, and the organization.
- Work Style: BMO values a diverse and inclusive work environment, with a focus on collaboration, innovation, and continuous learning. The company encourages employees to take ownership of their careers and supports their professional development and growth.
- Self-Assessment Questions:
- How do you embody BMO's values in your daily work?
- How do you approach collaboration and innovation in a team setting?
- How do you balance strategic thinking with hands-on data science work?
ASSUMPTION: Candidates who align with BMO's values and work style, and who can demonstrate their ability to thrive in a collaborative, innovative, and inclusive work environment, will be well-suited for this role.
⚠️ Potential Challenges
- Role-Specific Challenges: Managing a large team with diverse skills and experience levels, balancing strategic thinking with hands-on data science work, and navigating a complex, matrixed organization.
- Company-Specific Challenges: Working in a large, established financial institution with a history of change and transformation, and managing stakeholder expectations in a dynamic and evolving business environment.
- Industry-Specific Challenges: Keeping up with the latest trends and technologies in data science, analytics, and marketing technology, and navigating regulatory requirements and compliance challenges in the financial services industry.
ASSUMPTION: Candidates should be prepared to face these challenges head-on and demonstrate their ability to thrive in a dynamic and evolving work environment.
📈 Similar Roles Comparison
- Role Differentiation: This role focuses on marketing data science and analytics strategy, with a strong emphasis on leadership, stakeholder management, and team development. Similar roles may focus more on tactical data science work, or may be more focused on specific aspects of marketing analytics, such as customer insights or marketing effectiveness.
- Industry Context: In the financial services industry, data science and analytics play a critical role in driving customer acquisition, retention, and engagement. This role is unique in its focus on marketing data science and analytics strategy, and its emphasis on leadership and stakeholder management.
- Career Path Comparison: This role offers significant growth opportunities for the right candidate, with potential paths including expanding the team, taking on additional responsibilities, or moving into a more senior leadership role within the organization. Similar roles may offer different career paths, depending on the organization's structure and the specific focus of the role.
ASSUMPTION: Candidates should research the company and the role to understand the unique aspects of this position and how it aligns with their career goals and aspirations.
📝 Sample Projects
- Developing and implementing a marketing data science and analytics roadmap to support the strategic objectives of various business partners
- Building and deploying advanced analytics models to drive marketing effectiveness and improve customer acquisition and retention
- Leading a team of data science and analytics experts to develop and implement data-driven insights and solutions for marketing partners
- Collaborating with cross-functional teams to integrate marketing campaign data with business data and develop comprehensive reporting and analytics solutions
ASSUMPTION: Candidates should be prepared to provide specific examples of their experience and accomplishments in data science, analytics, and marketing technology, and to discuss how their skills and expertise align with the requirements of this role.
❓ Key Questions to Ask During Interview
- Role-Specific Questions:
- How does this role fit into the organization's overall data science and analytics strategy?
- What are the key priorities for the first 90 days in this role?
- How does the team collaborate with other departments and stakeholders within the organization?
- Team & Culture Questions:
- How would you describe the work style and culture of the team and the organization?
- What are the key strengths and areas for improvement within the team?
- Growth & Development Questions:
- What opportunities are there for professional development and growth within the role and the organization?
- How does the company support work-life balance for its employees?
ASSUMPTION: Candidates should prepare thoughtful and insightful questions that demonstrate their interest in the role and their understanding of the organization and its culture.
📌 Next Steps for Applicants
- To apply for this position:
- Submit your application through this link: [Application URL]
- Tailor your resume and cover letter to highlight your relevant experience and skills for this role
- Prepare for behavioral interview questions that focus on your leadership, problem-solving, and strategic thinking skills
- Research the company and the role to demonstrate your enthusiasm and understanding of the organization's mission and values
- Follow up with the hiring manager or recruiter one week after submitting your application, if you have not heard back
⚠️ Disclaimer: This job description contains AI-assisted information. Details should be verified directly with the employer before making decisions.
- Job Title: Managing Director, Marketing Analytics & Data Science
- Company: Bank of Montreal (BMO)
- Location: Toronto, Ontario, Canada
- Job Type: Regular, Full-Time
- Category: Data Analytics & Reporting
- Date Posted: April 15, 2025
- Experience Level: 10+ years
- Remote Status: On-site
🚀 Job Overview
Key aspects of this role include:
- Developing and leading the Marketing Data Science and Analytics strategy
- Collaborating with stakeholders to support strategic objectives
- Executing initiatives that develop data-driven insights
- Leveraging advanced analytics, AI, and machine learning to drive marketing strategy and effectiveness
- Managing a high-performing team of 20 digital marketing and analytics experts
ASSUMPTION: This role requires a strategic mindset, strong leadership skills, and deep expertise in data science, analytics, and marketing technology.
📋 Key Responsibilities
- Strategic Leadership: Develop and implement the Marketing Data Science and Analytics strategy, aligning it with business objectives and common capabilities.
- Stakeholder Management: Partner with CMOs, MCSI, CDAO, operational group/service leaders, and LOB DnA teams to understand their strategic objectives and provide trusted advisory services.
- Data-Driven Insights: Execute initiatives that develop data-driven insights on valuable opportunities with marketing and business partners.
- Model Development & Testing: Develop and test model-based proof of concepts and prototypes to assess feasibility and value-creation potential.
- Advanced Analytics: Leverage advanced analytics/AI to support marketing strategy, drive acquisition, develop customer insights, and enhance marketing effectiveness.
- Team Leadership: Lead, mentor, and develop the Data Science and Analytics Practice across multiple geographies, fostering a high-performance culture.
- Talent Acquisition & Development: Partner with Talent Acquisition to recruit, evaluate, hire talent, and invest in the talent within the organization.
ASSUMPTION: This role involves a mix of strategic planning, hands-on data science work, team leadership, and stakeholder management.
🎯 Required Qualifications
- Education: Bachelor's degree in Management Information Systems, Computer Science, Computer Engineering, or a related field. Advanced degree (e.g., MS, PhD) in a related field (e.g., Stats, Computer Science/Engineering) is preferred.
- Experience: Minimum 10 years of progressive work experience in Marketing, Computer Science, or IT, including technical leadership, project management, and management responsibilities. 5+ years of hands-on data science work experience and 5+ years of managing a data science team.
- Required Skills:
- Comprehensive practical and theoretical knowledge in Marketing Technology platforms
- Extensive hands-on leadership of Advanced Analytics teams utilizing coding languages such as SQL, SAS, Python, R, and Unix
- Experience with Salesforce tools (Marketing Cloud, Ad Studio, Interaction Studio), Marketing Automation tools (Persado, Marketo), and Analytics platforms (Google Analytics, Adobe Analytics)
- Familiarity with Marketing measurement and attribution solutions (Marketing Mix Modeling, Multi-Touch Attribution, Unified Measurement)
- Experience with supervised and unsupervised learning algorithms and their application to large data sets
- Relevant data engineering experience to architect/prototype solutions (e.g., ETL, apps, etc.)
- Experience with statistical programming languages/packages (Python, R, SAS, Scipy, etc.)
- Comfort working with the AWS-EMR and Hadoop ecosystems (Spark, MapReduce, Hive, etc.)
- Ability to partner cross-domain to solve problems and drive to recommendations
- Preferred Skills:
- Experience working in a fluid/start-up environment and with external clients
- Experience with Google Marketing and deployment of capabilities (value-based bidding models, building reporting that combines marketing campaign data with business data, Google’s next-generation AI and machine learning innovations supporting digital targeting and cyber controls)
ASSUMPTION: This role requires a well-rounded data science and analytics professional with strong leadership skills and a deep understanding of marketing technology platforms.
💰 Compensation & Benefits
- Salary Range: $190,000 - $215,000 CAD per year (target base salary range)
- Benefits:
- Health Insurance
- Tuition Reimbursement
- Accident Insurance
- Life Insurance
- Retirement Savings Plans
- Working Hours: Full-time, 40 hours per week
ASSUMPTION: The salary range provided is a target base salary range and may include a commission structure. Total compensation may include performance-based incentives, discretionary bonuses, and other perks and rewards.
📌 Applicant Insights
🔍 Company Context
- Industry: Financial Services
- Company Size: 10,001+ employees
- Founded: 1817 (as the Bank of Upper Canada)
- Company Description: BMO is a Canadian multinational investment bank and financial services company. It operates as a personal banking, commercial banking, and wealth management business with domestic operations in Canada and the United States.
- Company Specialties: Personal Banking, Commercial Banking, Wealth Management, Capital Markets, and Asset Management
📊 Role Analysis
- Career Level: Executive/Director level role, reporting directly to the Chief Marketing & Customer Experience Officer (CMCO)
- Reporting Structure: Leads a team of 20 digital marketing and analytics experts, with no direct reports mentioned
- Work Arrangement: On-site, full-time role, with no mention of hybrid or remote work arrangements
- Growth Opportunities: Potential growth opportunities include expanding the team, taking on additional responsibilities, or moving into a more senior leadership role within the organization
ASSUMPTION: This role offers significant growth opportunities for the right candidate, given the size and scope of the team and the strategic nature of the position.
🌍 Location & Work Environment
- Office Type: On-site, with no mention of remote or hybrid work arrangements
- Office Location(s): 33 Dundas Street West, Toronto, Ontario, Canada
- Geographic Context: Toronto is the capital city of the province of Ontario, with a population of approximately 2.9 million people. It is the largest city in Canada by population.
- Work Schedule: Full-time, 40 hours per week, with no mention of flexible hours or job sharing arrangements
ASSUMPTION: The on-site work arrangement may change in the future, given the company's size and the nature of the role.
💼 Interview & Application Insights
- Typical Process: The typical interview process for this role may include phone or video screens, followed by on-site interviews with relevant stakeholders, such as the hiring manager, team members, and other senior leaders within the organization.
- Key Assessment Areas: Technical skills (data science, analytics, and marketing technology), leadership skills, strategic thinking, and cultural fit
- Application Tips:
- Tailor your resume and cover letter to highlight your relevant experience and skills for this role
- Prepare for behavioral interview questions that focus on your leadership, problem-solving, and strategic thinking skills
- Research the company and the role to demonstrate your enthusiasm and understanding of the organization's mission and values
🛠️ Tools & Technologies
- AWS-EMR and Hadoop ecosystems (Spark, MapReduce, Hive, etc.)
- Statistical programming languages/packages (Python, R, SAS, Scipy, etc.)
- Marketing Technology platforms (Salesforce, Marketo, Google Analytics, Adobe Analytics)
- Data engineering tools and frameworks (ETL, ETL tools, data warehousing, data integration)
👔 Cultural Fit Considerations
- Company Values: BMO's values include integrity, humility, accountability, agility, and collaboration. The company seeks employees who embody these values and are committed to driving positive change for customers, communities, and the organization.
- Work Style: BMO values a diverse and inclusive work environment, with a focus on collaboration, innovation, and continuous learning. The company encourages employees to take ownership of their careers and supports their professional development and growth.
- Self-Assessment Questions:
- How do you embody BMO's values in your daily work?
- How do you approach collaboration and innovation in a team setting?
- How do you balance strategic thinking with hands-on data science work?
ASSUMPTION: Candidates who align with BMO's values and work style, and who can demonstrate their ability to thrive in a collaborative, innovative, and inclusive work environment, will be well-suited for this role.
⚠️ Potential Challenges
- Role-Specific Challenges: Managing a large team with diverse skills and experience levels, balancing strategic thinking with hands-on data science work, and navigating a complex, matrixed organization.
- Company-Specific Challenges: Working in a large, established financial institution with a history of change and transformation, and managing stakeholder expectations in a dynamic and evolving business environment.
- Industry-Specific Challenges: Keeping up with the latest trends and technologies in data science, analytics, and marketing technology, and navigating regulatory requirements and compliance challenges in the financial services industry.
ASSUMPTION: Candidates should be prepared to face these challenges head-on and demonstrate their ability to thrive in a dynamic and evolving work environment.
📈 Similar Roles Comparison
- Role Differentiation: This role focuses on marketing data science and analytics strategy, with a strong emphasis on leadership, stakeholder management, and team development. Similar roles may focus more on tactical data science work, or may be more focused on specific aspects of marketing analytics, such as customer insights or marketing effectiveness.
- Industry Context: In the financial services industry, data science and analytics play a critical role in driving customer acquisition, retention, and engagement. This role is unique in its focus on marketing data science and analytics strategy, and its emphasis on leadership and stakeholder management.
- Career Path Comparison: This role offers significant growth opportunities for the right candidate, with potential paths including expanding the team, taking on additional responsibilities, or moving into a more senior leadership role within the organization. Similar roles may offer different career paths, depending on the organization's structure and the specific focus of the role.
ASSUMPTION: Candidates should research the company and the role to understand the unique aspects of this position and how it aligns with their career goals and aspirations.
📝 Sample Projects
- Developing and implementing a marketing data science and analytics roadmap to support the strategic objectives of various business partners
- Building and deploying advanced analytics models to drive marketing effectiveness and improve customer acquisition and retention
- Leading a team of data science and analytics experts to develop and implement data-driven insights and solutions for marketing partners
- Collaborating with cross-functional teams to integrate marketing campaign data with business data and develop comprehensive reporting and analytics solutions
ASSUMPTION: Candidates should be prepared to provide specific examples of their experience and accomplishments in data science, analytics, and marketing technology, and to discuss how their skills and expertise align with the requirements of this role.
❓ Key Questions to Ask During Interview
- Role-Specific Questions:
- How does this role fit into the organization's overall data science and analytics strategy?
- What are the key priorities for the first 90 days in this role?
- How does the team collaborate with other departments and stakeholders within the organization?
- Team & Culture Questions:
- How would you describe the work style and culture of the team and the organization?
- What are the key strengths and areas for improvement within the team?
- Growth & Development Questions:
- What opportunities are there for professional development and growth within the role and the organization?
- How does the company support work-life balance for its employees?
ASSUMPTION: Candidates should prepare thoughtful and insightful questions that demonstrate their interest in the role and their understanding of the organization and its culture.
📌 Next Steps for Applicants
- To apply for this position:
- Submit your application through this link: [Application URL]
- Tailor your resume and cover letter to highlight your relevant experience and skills for this role
- Prepare for behavioral interview questions that focus on your leadership, problem-solving, and strategic thinking skills
- Research the company and the role to demonstrate your enthusiasm and understanding of the organization's mission and values
- Follow up with the hiring manager or recruiter one week after submitting your application, if you have not heard back
⚠️ Disclaimer: This job description contains AI-assisted information. Details should be verified directly with the employer before making decisions.