Data Science Senior Manager

4 weeks ago

Toronto, Canada Scotiabank Full time

The Data Science Senior Manager role will focus on building and managing end-to-end Machine Learning Operations solutions within a cross-functional Agile Scrum lab for fraud detection and prevention. This role will be supporting machine learning model development, implementation, and monitoring, as well as model governance activities for both in-house and external vendor fraud models.

Is this role right for you? In this role you will:

Collaborate with stakeholders including Operations, Analytics and Data Science partners, as well as Payments, Scotia Digital, and IT&S partners to identify improvement opportunities and drive incremental business value in reducing fraud risks Leverage distributed computing tools Beam, BigQuery, Hive, Spark) for analysis, data mining and modeling Collaborate with technology / engineering, analytics, and operational teams to deploy fraud detection and prevention models and algorithms in production across different products and channels Create and apply model validation strategies to measure model effectiveness, conduct A/B testing, and deliver ongoing enhancements Prepare detailed documentation to outline data sources, models and algorithms used and developed Present results to business line stakeholders and help implement data-driven decisioning, automation and associated operational change management with real business impact Champion a customer focused culture to deepen client relationship and leverage broader inter-departmental relationships, as well as knowledge of systems and processes Leverage Scrum framework for iterative and incremental agile development of machine learning product features, participate in sprint review, planning, and daily scrum ceremonies Understand how the Bank’s risk appetite and risk culture should be considered in day-to-day activities and decisions

Do you have the skills that will enable you to succeed in this role? We’d love to work with you if you have:

Post-secondary degree in relevant STEM discipline (Computer Science, Electrical/Computer/Software Engineering, and Statistics/Mathematics) and/or 2+ year similar hands-on experience preferred Experience with machine learning, statistical techniques, as well as model testing and validation Experience cleaning, transforming and visualizing large data sets working with various data formats unstructured logs, XML, JSON, flat files, audio, image) Solid SQL skills for querying relational databases SQL Server, DB2, MySQL) Programming skills in Python, Java or Scala Hands-on experience with Big Data ecosystem tools Beam, BigQuery, Hive, Spark) preferred Expertise with Docker or Kubernetes is an asset Experience with various services on Google Cloud Platform is an asset Experience deploying models into productions as streaming application, Rest APIs, batch jobs or dashboards is an asset Knowledge of industry trends regarding fraud and experience in fraud detection and prevention is an asset

What’s in it for you?

We have an exciting opportunity to join a team of passionate individuals at Scotiabank that are enthusiastic about building trust and enhancing the financial security of our customers. This role will be directly working as a part of a Fraud Management AI lab alongside technology partners to develop and implement innovative MLOps solutions on the cloud to solve the challenging and dynamically evolving fraud business problems. This role will position the candidate well for leadership exposure, growth and networking opportunities given the nature of the cross-functional work and the overarching business domains in scope of Fraud Management. This role has a flexible hybrid working schedule, with a modernized activity-based in-office ecosystem located at the downtown core of Toronto.

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