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BMO Financial Group Sr Manager - Data Science in Toronto, Ontario

Description:

Applies knowledge of advanced analytics algorithms and technologies (e.g. machine learning, deep learning, artificial intelligence) to deliver better predictions and/or intelligent automation that enable smarter business decisions, improved customer experience and drive productivity for our business. Strong communication and story-telling skills to summarize statistical/algorithmic findings to draw business conclusions, and present actionable insight in a way that resonates with business/groups. Drives innovation through the development of Data & AI products that can be leveraged across the organization and establishes best practices in in alignment with Data & AI governance frameworks of BMO.

  • Manages people and leads a team capable of delivering the desired business results.

  • Influences and negotiates to achieve business objectives.

  • Identifies emerging issues and trends to inform decision-making.

  • Provides strategic input into business decisions as a trusted advisor.

  • Makes recommendations to senior leaders on strategy and new initiatives, based on an in-depth understanding of the business/group.

  • Acts as a subject matter expert on relevant regulations and policies.

  • Networks with industry contacts to gain competitive insights and best practices.

  • Leads discovery process with stakeholders to identify business requirements and expected outcome and to select relevant sources of data/information.

  • Manages resources and leads the execution of strategic initiatives to deliver on business and financial goals.

  • Helps determine business priorities and best sequence for execution of business/group strategy.

  • Develops the business case by identifying needs, analysing potential options and assessing expected return on investment.

  • Recommends business priorities, advises on resource requirements and develops roadmap for strategic execution.

  • Makes strategic recommendations on data collection, integration and retention requirements incorporating business requirements and knowledge of best practices.

  • Structures loosely defined and complex business problems; determines new experimentation methods and statistical techniques to design solutions.

  • Acts as the prime subject matter expert for internal/external stakeholders.

  • Identifies/creates the appropriate algorithm to discover patterns.

  • Drives analytics innovation; poses open-ended questions, explores new ideas, and chooses appropriate techniques for solving business problems.

  • Oversees the development and delivery of tools and training for data and analytics.

  • Diagnoses and resolves predictive / analytical model performance issues while monitoring system performance and implementation of efficiency improvements.

  • Leads change management programs of varying scope and type, including readiness assessments, planning, stakeholder management, execution, evaluation and sustainment of initiatives.

  • Leads the development of the communication strategy focusing on positively influencing or changing behaviour.

  • Applies innovative and best practices to advanced analytics services to ensure high quality standards.

  • Sets up change control and testing processes to ensure the quality and consistency of ongoing maintenance work.

  • Designs and implements policies and procedures around new data sets to ensure data quality, consistency, repeatability, and accuracy of insights.

  • Develops analytical solutions and makes recommendations based on an understanding of the business strategy and stakeholder needs.

  • Provides advice and guidance to assigned business/group on implementation of analytical solutions.

  • Works with stakeholders to identify the business requirements, understand the distinct problems, and the expected outcome and models and frames business scenarios which impact critical business processes and/or decisions.

  • Works with various data owners to discover and select available data sources from internal sources and external vendors (e.g. lending system, payment system, external credit rating system, and alternative data) to fulfill analytical needs.

  • Applies scripting / programming skills to assemble various types of source data (unstructured, semi-structured, and structured) into well-prepared datasets with multiple levels of granularities (e.g., demographics, customers, products, transactions).

  • Develops agreed analytical solution 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, refine hypotheses.

  • Summarizes statistical findings and draws conclusions and presents actionable business recommendations. Presents findings & recommendations in a simple, clear way to drive action.

  • Documents data flow, systems and processes in data collection to improve efficiency and apply use cases.

  • Performs experimental design approaches to validate finding or test hypotheses.

  • Uses the appropriate algorithms to discover patterns.

  • Builds effective relationships with internal/external stakeholders. Ensures alignment between stakeholders.

  • Supports development of tools and delivers training for data analytics and AI.

  • Supports development and execution of strategic initiatives in collaboration with internal and external stakeholders.

  • Leads/participates in the design, implementation and management of core business/group processes.

  • Operates at a group/enterprise-wide level and serves as a specialist resource to senior leaders and stakeholders.

  • Applies expertise and thinks creatively to address unique or ambiguous situations and to find solutions to problems that can be complex and non-routine.

  • Implements changes in response to shifting trends.

  • Broader work or accountabilities may be assigned as needed.

Qualifications:

  • Typically 7 years of relevant experience and/or certification in related field of study or an equivalent combination of education and experience.

  • Advanced degree (Ph.D. preferred) in Computer Science, Mathematics, Physics, Engineering, Statistics, or other quantitative disciplines and/or equivalent experience.

  • In depth experience using machine learning algorithms.

  • Experience with distributed computing language (e.g. Hive /Hadoop/ Spark) & cloud technologies (e.g. AWS Sagemaker, AzureML).

  • Experience with programming languages (e.g. SQL, Python, R,SAS, SPSS, , Perl) and machine learning /deep learning algorithms/packages (e.g. XGBoost, H2O, SparkML).

  • Seasoned professional with a combination of education, experience and industry knowledge.

  • Verbal & written communication skills - In-depth /Expert.

  • Analytical and problem solving skills - In-depth / Expert.

  • Influence skills - In-depth / Expert.

  • Collaboration & team skills; with a focus on cross-group collaboration - In-depth / Expert.

  • Able to manage ambiguity.

  • Data driven decision making - In-depth / Expert.

We’re here to help

At BMO we have a shared purpose; we put the customer at the centre of everything we do – helping people is in our DNA. For 200 years we have thought about the future—the future of our customers, our communities and our people. We help our customers and our communities by working together, innovating and pushing boundaries to bring them our very best every day. Together we’re changing the way people think about a bank.

As a member of the BMO team you are valued, respected and heard, and you have more ways to grow and make an impact. We strive to help you make an impact from day one – for yourself and our customers. We’ll support you with the tools and resources you need to reach new milestones, as you help our customers reach theirs. From in-depth training and coaching, to manager support and network- building opportunities, we’ll help you gain valuable experience, and broaden your skillset.

To find out more visit us at https://bmocareers.com .

BMO is committed to an inclusive, equitable and accessible workplace. By learning from each other’s differences, we gain strength through our people and our perspectives. Accommodations are available on request for candidates taking part in all aspects of the selection process. To request accommodation, please contact your recruiter.

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Job Field:

Data Sciences

Job Schedule:

full-time

Primary Location:

Canada-Ontario-Toronto

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