Sr Manager (Sr Data Scientist) Business Banking Credit Risk (12 month contract)

Scotiabank; Toronto; On-site; CAD 100,000 - 140,000; Full time

Job summary

Join a leading bank as a Sr Data Scientist focused on Business Banking Credit Risk. In this role, you will analyze complex data, drive strategic insights, and support the development of robust analytics frameworks. Your expertise in machine learning and data analytics will contribute to informed decision-making and optimized business outcomes.

Qualifications

• 5+ years of relevant work experience in data analytics.
• Experience with Python, SQL or SAS.
• Strong understanding of predictive analytics and machine learning techniques.

Responsibilities

• Design and implement data extraction and transformation workflows.
• Apply statistical, machine learning, and AI techniques to solve business problems.
• Monitor Business Banking portfolio indicators and provide data-driven insights.

Skills

Python

SQL

SAS

Predictive Analytics

Machine Learning

Data Visualization

Education

Post-secondary education in Computer Science, Engineering, or Mathematics

Master’s degree preferred

Tools

Power BI

Tableau

GCP

Job description

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Requisition ID: 229348

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

(Sr Manager) Sr Data Scientist, Business Banking Credit Risk

The Sr Data Scientist, Business Banking Credit Risk will work closely with senior management, GRM colleagues, business line leads, and a diverse set of stakeholders to generate insights and deliver strategic recommendations. The incumbent will drive analyses, support oversight, and strategic thought leadership across Business Banking portfolios, segments and industries, ensuring business strategies, plans and initiatives are supported in compliance with governing regulations, internal policies and procedures.

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

• Design and implement data extraction and transformation workflows to prepare structured and unstructured data for advanced analytics. Ensure data quality, consistency, and readiness for modeling and insight generation.
• Leverage modern data science tools and cloud-based platforms to streamline model development, experimentation, and deployment. Contribute to the evolution of scalable, reproducible analytics environments that support business decision-making.
• Work closely with data engineers, business stakeholders, and product teams to translate complex data into actionable insights. Align analytical outputs with strategic objectives and regulatory requirements.
• Apply cutting-edge statistical, machine learning, and AI techniques to solve business problems. Promote best practices in model validation, interpretability, and governance to ensure robust and ethical use of data.
• The incumbent will support oversight and analytics across Business Banking (BB) portfolios, segments, and industries, ensuring that data infrastructure and engineering practices enable business strategies in compliance with internal policies and external regulations.
• Monitor Business Banking portfolio indicators, proactively analyzing performance alongside macro-economic and external trends; collaborate with the Lending Policy and Governance and GRM colleagues to establish recommendations based on data-driven observations and analyses.
• Develop innovative and effective approaches, applying statistical and predictive modeling techniques to solve analytics challenges.
• Present and depict the rationale of findings in easy-to-understand terms for a non-technical audience.
• Utilize external data sources to enhance insights and improve model accuracy, while effectively communicating results and methodologies to stakeholders and team members.
• Prepare detailed documentation to outline data sources, models and algorithms used and developed
• Complete competitive / business environment research and benchmarking to determine emerging issues, trends and analyze the impact / implications of those trends.
• Measure and monitor credit score and policy changes across the credit life cycle (adjudication, customer management and collections) with a focus on independent analysis of the risk-return trade-off.
• Collaborate with GRM colleagues to improve portfolio monitoring and account management capabilities through integration of new models and frameworks.
• Support annual strategic planning process through thought leadership on implications to KPIs and risk related metrics, based on business objectives and growth plans.
• Enable and deliver analyses and strategy development for Business Banking Credit Risk initiatives related to Capital optimization and Risk Adjusted Return on Capital.
• Execute day-to-day activities in a manner consistent with the Bank’s risk culture and the relevant risk appetite statement and limits. Communicate the Bank’s risk culture and risk appetite statement.
• Create an environment in which his/her team pursues effective and efficient operations of his/her respective areas, while ensuring the adequacy, adherence to and effectiveness of day-to-day business controls to meet obligations with respect to operational risk, regulatory compliance risk, AML/ATF risk and conduct risk, including but not limited to responsibilities under the Operational Risk Management Framework, Regulatory Compliance Risk Management Framework, AML/ATF Handbook and the Guidelines for Business Conduct.
• Build a high-performance environment and implement a people strategy that attracts, retains, develops and motivates their team by fostering an inclusive work environment, communicating vison/values/business strategy and managing succession and development planning for the team.

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 education focused on Computer Science, Electrical/Computer/Software Engineering or Mathematics; master’s degree preferred.
• 5+ years of relevant work experience in data analytics.
• 5+ years of experience with Python, SQL or SAS.
• Familiarity working with GCP or other major cloud providers.
• Strong understanding of predictive analytics and machine learning techniques, including Random Forests, Neural Networks, NLP, clustering, and other similar methods, with hands-on experience implementing common algorithms in Python and GCP.
• Solid analytical skills with comfortability working with large amounts of information and translating data into clear and concise findings.
• Experience using and implementing visualization tools such as Power Bi and/or Tableau.
• Knowledge of Business Banking products and services is an asset.
• Strong verbal and writtencommunication and interpersonal skills, with strong ability to present recommendationsin a client-facing setting.
• Knowledge in data engineering and data pipeline skills is desirable.
• Exceptional problem-solving skills, with ability to manage ambiguity.
• Highly organized with proven ability to make decisions in time pressured environment.

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.