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BMO Financial Group Data Scientist-Fraud Analytics in Toronto, Ontario

Description:

The Financial CrimesUnit (FCU) brings together our Cybersecurity, Fraud and Physical Securitycapabilities to address the ever-growing and increasingly complex globalsecurity environment. It is a highly collaborative effort that greatly enhancesBMO’s ability to rapidly prevent, detect, respond to, and recover from allsecurity threats. This position offers a unique experience to learn fromexperienced leaders in the industry, join a team building the 21st centurymodel for security and helping grow the good by protecting our customers andcommunities.

The Data Scientist applies knowledge ofadvanced analytics, machine learning (ML) and artificial intelligence (AI) todeliver statistical analytics, predictive models and intelligent automationthat enable smarter business decisions, improve customer experience and drive productivityfor our business. Use a mixture of datascience and data engineering skills to investigate and research structured andun-structured data, while working with business and technology partners toidentify the most appropriate data-sources and information required to achievethe business goals.

Able to use strongcommunication and story-telling skills to summarize statistical/algorithmicfindings and present actionable insights, in a way that resonates withbusiness/groups.Drives innovationthrough the development of Data & AI products that can be leveraged acrossthe organization and establishes and follows best practices in alignment withData & AI governance frameworks of BMO. Take ownership, monitorthe usage and lead the improvements roadmap for the existing production models,already deployed in the production environment.

  • Acts as a trusted advisor of Analytics, ML, and AI fields.

  • 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.

  • Understands and analyzes complex business problem, then formulates data-driven hypotheses to drive business value through data-science specific approach.

  • Recommends and implements solutions based on analysis of issues and implications for the business.

  • Highly proficient in building ML and AI models and solutions, from ground zero up. Experience in creating and maintaining production quality systems is an asset.

  • Comfortable to work in a fluid requirement landscape to explore and ideate new analytics/ML/AI use-cases with the business partners.

  • Assists in the development of strategic plans.

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

  • Builds effective relationships with internal/external stakeholders.

  • Defines innovative data solutions to loosely defined business problems by leveraging pattern detection over potentially large datasets.

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

  • Works with various data owners to discover and select available data sources from internal sources and external vendors to fulfill analytical needs.

  • Applies scripting / programming skills to assemble various types of source data (unstructured, semi-structured, and structured) into new datasets, conduct data analysis and data preparation activities, use feature engineering techniques, frame the hypothesis, implement the target and the metrics functions. Very proficient in model building and hyper-parameter tuning.

  • Focus is primarily on FCU within BMO; may have broader, enterprise-wide focus.

  • Works independently and regularly handles non-routine situations.

  • Broader work or accountabilities may be assigned as needed.

Qualifications:

  • Relevant experience and post-secondary degree in data science or an equivalent combination of education and experience.

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

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

  • Experience with programming languages (SQL, Python, R) and machine learning /deep learning algorithms/packages (Python Packages, TensorFlow, Keras).

  • Proficiency in statistical analysis, quantitative analytics, forecasting/predictive analytics, multivariate testing, and optimization algorithms.

  • Verbal & written communication skills - In-depth.

  • Collaboration & team skills - In-depth.

  • Analytical and problem solving skills - In-depth.

  • Influence skills - In-depth.

  • Data driven decision making - In-depth

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.

Job Field:

Data Sciences

Job Schedule:

full-time

Primary Location:

Canada-Ontario-Toronto

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