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Director & Lead Data Scientist
| Company | Bank of Montreal |
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| Location | Toronto, ON, Canada |
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| Salary | $124200 – $231000 |
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| Type | Full-Time |
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| Degrees | |
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| Experience Level | Expert or higher |
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Requirements
- Expert level of proficiency in Mathematics, statistics & operations research
- Deep learning
- Machine learning
- Trust, bias, and ethics
- Creative thinking
- Critical thinking
- Big data
- Data visualization
- Computational thinking and programming
- Data wrangling
- Data preprocessing
- Creative reasoning
- Verbal & written communication skills
- Analytical and problem-solving skills
- Influence skills
- Collaboration & team skills, with a focus on cross-group collaboration
- Ability to manage ambiguity
- Data-driven decision making
- Typically 9+ years of relevant experience and/or certification in a related field of study or an equivalent combination of education and experience
- Seasoned expert with extensive industry knowledge
- Technical leader viewed as a thought leader for innovation.
Responsibilities
- Manage a team of data scientists to bring advanced analytical algorithms and modeling approaches to solving BMO Commercial Banking business problems.
- Partner with stakeholders across the Commercial Bank to uncover opportunities and work with the Data Science team and Sr. Manager, Strategy and Governance to develop a prioritized roadmap that aligns with BMO Commercial and BMO’s overall strategic objectives.
- Collaborate with the Data Engineering and Model Operations team to source data required for model development and operations.
- Develop solutions appropriate to the problem statements, in partnership with stakeholders, to ensure that solutions integrate optimally with business processes.
- Work with the Sr. Manager, Strategy and Governance to ensure that various governance requirements are met, including but not limited to Responsible AI, Model Validation, Legal, Regulatory, and Compliance requirements.
- Prepare the appropriate artifacts to fulfill the bank’s Model Validation and Model Risk Management requirements, when required.
- Along with the Data Engineering and Model Operations team, provide oversight and ongoing monitoring over deployed analytical assets and models, take appropriate action when required, and support inquiries from model users, leadership, and 2nd line groups.
- Use data mining and extracting usable data from valuable data sources to assess the feasibility of AI/ML solutions for improved processing and usage of organization data.
- Conduct large-scale analysis of information to discover patterns and trends by combining different modules and algorithms.
- Use analysis to provide recommendations and advice for business leaders to maintain market competitiveness.
- Develop prediction systems and machine learning algorithms.
- Investigate additional technologies and tools for developing innovative data solutions for business stakeholders.
- Collaborate with the product team and partners to understand and provide data-driven decision making, business planning, and future roadmap.
- Foster a culture aligned to BMO purpose, values, and strategy, and role model BMO values and behaviors in all that they do and ensure alignment between values and behavior that fosters diversity and inclusion.
- Regularly connect work to BMO’s purpose, set inspirational goals, define clear expected outcomes, and ensure clear accountability for follow-through.
- Build interdependent teams that collaborate across functional and operating groups to create the highest value for all stakeholders.
- Attract, retain, and enable the career development of top talent.
- Improve team performance, recognize and reward performance, coach employees, support their development, and manage poor performance.
- Operate at a group/enterprise-wide level and serve as a senior specialist resource across BMO.
- Apply expertise and think creatively to address unique or ambiguous situations and find solutions to multiple, interdependent, complex problems.
- Communicate abstract concepts in simple terms.
- Foster strong internal and external networks and work with and across multiple teams to achieve business objectives.
- Anticipate trends and respond by implementing appropriate changes.
- Broader work or accountabilities may be assigned as needed.
Preferred Qualifications
No preferred qualifications provided.
