Requisition ID: 147974
Join a purpose driven winning team, committed to results, in an inclusive and high-performing culture.
Purpose of Job:
GRM Retail Credit Risk aims to be an industry leader in developing innovative solutions for Retail Banking. This is accomplished using advanced analytics, agile principles and disciplined risk governance. To align with its departmental mission to modernize Credit Risk, the Analytics team acts as an idea incubator and analytical use cases accelerator, leveraging non-traditional data, advanced tools and enterprise systems. The team relies on Credit Science expertise and key business partners to provide consulting services within GRM and help build the next generation of retail credit solutions at Scotiabank.
The Senior Data Scientist will support key projects aimed at accelerating benefits for customers and the bank, leveraging enterprise-level data management tools and advanced analytics. She/he will work closely with Global Risk teams, the business lines, Digital Banking and IT to apply advanced analytics techniques and tools, as well as explore ideas to enhance retail lending portfolios within risk appetite thresholds. The candidate will help identify and recommend opportunities to deliver innovative credit offers based on risk-reward framework and the GRM’s digital strategy.
The role requires rigorous logical thinking, curiosity, flexibility and great teamwork abilities. The candidate will be at the intersection of math/stats, computer science, communication, and domain knowledge in Risk Management, Finance or Marketing. She/he will take a leading role in agile rapid labs and risk-reward strategy development to drive innovation and digital transformation throughout the Bank and Global Risk Management.
WHAT’S IN IT FOR YOU?
- Opportunity to make an impact in the digital transformation of Scotiabank
- Exposure to different business lines where analytics techniques are being applied
- Hands-on practical projects which provide an opportunity to gain new knowledge and develop skills
- A compensation program with competitive salary, opportunities for annual performance incentives based on performance thresholds, a competitive benefits program and continuing education programs
University degree in relevant STEM discipline (Science, Technology, Engineering and Mathematics)
- Ability to work with large volumes of structured and unstructured non-traditional data
- Knowledge of big data tools, programming languages such as Hive, SQL, R, Python, Spark, data visualization tools such as Tableau, PowerBI
- Working experience with machine learning and other AI techniques for strategy design
- Experience with collaboration tools (i.e. Jira, Confluence) to connect multiple stakeholders
- Strong collaboration skills with ability to translate technical knowledge into business value
- Effective communication skills with ability to prepare project documentation and presentations
- Excellent interpersonal skills with ability to understand and navigate team dynamics
Research, develop, and implement innovative credit solutions using advanced and predictive data analytics, big data, and AI/machine learning techniques to support growth and strategy optimization opportunities within the Caribbean and Central American markets
- Lead and drive strategy design thinking with business partners, subject matter experts, and external consultants to further enhance risk-reward predictions, customer segmentation, credit limits setting, risk-based pricing, and fraud detection through full credit lifecycle for retail and small business (e.g. credit origination, account management, collections strategies and/or other credit solutions)
- Leverage Agile framework to lead, prioritize and deploy data science projects. Co-ordinate with cross-functional teams to align with project scope and meet project timelines.
- Collaborate with Toronto and local business partners to implement new credit solutions in selected markets. Track and monitor key performance indicators to accelerate scalable deployment across key markets in an agile and rapid environment
- Partner with Scotiabank Rapid Laps, Digital team, and other analytics areas within the bank to support use case development and deployment
- Revamp existing data infrastructure and support migration to cloud server
- Work with Business Intelligence team and key stakeholders to define data engineering, visualization and machine learning data requirement to support strategy design blueprints
- Participate proactively in developing and maintaining team standards, tools and best practices
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. 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.