Manager - Data Analytics, First Nations / Inuit / Métis

October 11

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BMO U.S.

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Commercial Banking • Personal Banking • Small Business Banking

5001 - 10000

Description

• Uses advanced analytical algorithms and technologies (e.g. machine learning, deep learning, artificial intelligence) to mine and analyze large sets of structured and unstructured data to obtain insights. • Designs and constructs new processes for modeling data. • Develops predictive models and leverages big data technology to design solutions that deliver smarter business decisions, improve customer experience, and drive productivity. • Collaborates with other data and analytics professionals and teams to optimize, refine and scale analysis into mature analytics solutions. • Plays an active role in the futuristic display of data, and advancement of innovative data strategies to understand consumer trends and address business problems. • Uses data mining and extracting usable data from valuable data sources to assess feasibility of AI/ML solutions for improved processing and usage of organization data. • Conducts large-scale analysis of information to discover patterns and trends by combining different modules and algorithms. • Uses analysis to provide recommendations and advice for business leaders to maintain market competitiveness. • Develops prediction systems and machine learning algorithms. • Investigates additional technologies and tools for developing innovative data solutions for business stakeholders. • Collaborate together with the product team and partners to understand and provide data-driven decision making, business planning and future roadmap. • Focus is primarily on business/group within BMO; may have broader, enterprise-wide focus. • Provides specialized consulting, analytical and technical support. • Exercises judgment to identify, diagnose, and solve problems within given rules. • Works independently and regularly handles non-routine situations. • Broader work or accountabilities may be assigned as needed.

Requirements

• Intermediate level of proficiency: Mathematics, statistics & operations research. • Deep learning. • Machine learning. • Trust, bias and ethics. • Creative thinking. • Critical thinking. • Advanced level of proficiency: Big data. • Data visualization. • Computational thinking and programming. • Data wrangling. • Data preprocessing. • Creative reasoning. • Verbal & written communication skills. • Collaboration & team skills. • Analytical and problem solving skills. • Influence skills. • Data driven decision making. • Typically between 5 - 7 years of relevant experience and post-secondary degree in related field of study or an equivalent combination of education and experience.

Benefits

• health insurance • tuition reimbursement • accident and life insurance • retirement savings plans