Job description

Requisition ID: 163105


Join a purpose driven winning team, committed to results, in an inclusive and high-performing culture.


Purpose


The GBM Analytics team has been focused on building out a library of sophisticated models and the requisite infrastructure to enhance data-driven decision making across the bank, with a focus on businesses in Capital Markets and Group Treasury. Our team consists of highly accomplished business professionals who blend expertise in Mathematics, Computer science, Statistics, Capital markets and Treasury, to architect and deliver innovative technical solutions driving business value. Our work spans a broad technology stack involving the development of data pipelines, predictive models and data visualizations.


We are seeking an enthusiastic professional with experience in applied Machine Learning, AI and requisite domain knowledge to continue to build out and lead our modeling efforts in some of projects within the GBM Analytics portfolio. This is a senior role within the group where the successful individual should be adept at communicating to senior stakeholders across the bank translating complex concepts into actionable business insights as well as managing competing priorities and trade-offs.


Key Accountabilities


  • Define, build and manage the entire lifecycle of a Machine Learning/Analytics project from Scoping to Deployment with a delivery oriented approach, collaborating with cross-functional teams.
  • Design, build and implement models to solve business problems using advanced statistical & machine learning techniques.
  • Distill and transform data-driven insights into a tangible Product.
  • Lead and guide a change mandate across the team on innovative use of Alternative Data sources.
  • Motivation to learn about new advancements in Machine Learning as well as new domains in Capital Markets.


Technical Qualifications


  • A technical undergraduate degree in Mathematics, Computer Science, Statistics or similar. Postgraduate degree specialized in Data Science/Machine Learning preferred.
  • At least 3 years of hands-on experience as a Data Scientist.
  • Proficiency in Python, SQL and Git workflow.
  • Hands-on experience in working with and reconciling big data sets using technologies such as Hive/PySpark.
  • Familiarity with advanced machine learning tools and libraries.
  • Expertise in end-to-end advanced Machine Learning processes in various platforms including Cloud(GCP preferred).
  • Expertise in Time-Series modeling.
  • Strong understanding of Machine Learning model explainability and interpretation.
  • Experience with visualization tools such as PowerBI, Plotly.
  • Strong presentation skills and experience with building a compelling narrative based on complex data and analytics.


Nice To Have


  • Experience with building and maintaining data pipelines.
  • Experience with UNIX tools and shell scripting.
  • Preference will be given to candidates with experience in Capital Markets, Treasury or other relevant field.


Location(s): Canada : Ontario : Toronto


Scotiabank is a leading bank in the Americas. Guided by our purpose: for every future, we help our customers, their families and their communities achieve success through a broad range of advice, products and services, including personal and commercial banking, wealth management and private banking, corporate and investment banking, and capital markets.


At Scotiabank, we value the unique skills and experiences each individual brings to the Bank, and are committed to creating and maintaining an inclusive and accessible environment for everyone. If you require accommodation (including, but not limited to, an accessible interview site, alternate format documents, ASL Interpreter, or Assistive Technology) during the recruitment and selection process, please let our Recruitment team know. If you require technical assistance, please click here. Candidates must apply directly online to be considered for this role. We thank all applicants for their interest in a career at Scotiabank; however, only those candidates who are selected for an interview will be contacted.

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