Senior Manager, Advanced Analytics

TD•Toronto, ON

2d•Onsite

About The Position

Forecast Methodologies is part of TBSM's Enterprise Stress Testing (EST), responsible for central ownership and analysis of the balance sheet and income Statement Forecast Methodologies for EWST & MST. The Canadian Line of Business Vertical team within EST is a cross-functional group supporting the end-to-end stress testing functions for TD's Canadian businesses including P&C, Wealth, Insurance & NII. Our work encompasses multiple workstreams including data aggregation, model execution, model development, reporting/analytics, governance, and supporting regulatory requirements. Breadth & Depth Act as subject matter expert on SAS (primarily) or Python, MLE, automation, and results aggregation. Developing & maintaining the backend automation infrastructure for the team's model development & execution commitments. Supporting the team's ongoing efforts towards operational resilience through the development of robust automation processes and the promotion of sound programming practices. Development and implementation of best practices relating to data aggregation, modelling, and stress testing processes. Driving bespoke solutions for modelling endeavors where available data is limited, noisy, incomplete, or otherwise unfit for use as-is. Maintain up-to-date documentation on data processing steps and conventions. Develop & maintain team-wide programming best practices, style guide, and other tools to help drive consistency and reliability of modelling outcomes. Hands on work with ad-hoc analyses and assessment of data quality. Lead the preparation of ad hoc analysis for senior leadership. Deepen our team's understanding and recordkeeping of metadata and qualitative attributes relating to our data sources, including known deficiencies and other details relevant to a data source's suitability for modelling. Uses sophisticated analytical thought to exercise judgement and identify solutions. Communicates difficult concepts; converts information to compelling business context and advice; influences and gains alignment across increasingly senior stakeholders. Must be able to work with minimal supervision in an unstructured and fast-paced environment.

Requirements

High degree of SAS programming proficiency.
Experience with using SAS for enterprise data processing & automation is critical to the success of the candidate in this role.
Undergraduate degree required.
7+ years relevant experience.
In-depth knowledge of quantitative models and statistical analysis.
Data analytics competencies supported by experience in traversing large data sets to perform analytics/drive business insights.
Experience with Stress Testing & Knowledge of PPNR requirements.
Advanced knowledge of quantitative forecasting models, financial analysis techniques and methodologies.
Proven ability to employ complex analytical tools and statistics to perform analysis and forecasting of financial and other business information.
Demonstrated ability to drive transformation and change.
Excellent written and verbal communication skills are essential.
Ability to successfully plan, develop, lead, and execute projects.
Ability to effectively interpret, select appropriate techniques, take independent action, communicate, and follow-through.
Proven ability to manage competing priorities effectively, making good decisions based on business priorities and objectives.
Proficiency with MS Office Suite, including a strong competency in MS Excel and Power BI.

Nice To Haves

Experience with adjacent programming technologies (R, Python) will be considered an asset.
Advanced technical degree preferred (e.g., math, physics, engineering, finance or computer science).
Graduate's degree preferred.
Canadian P&C and/or Canadian Wealth and/or NII experience or associated finance support considered beneficial.

Responsibilities

Act as subject matter expert on SAS (primarily) or Python, MLE, automation, and results aggregation.
Developing & maintaining the backend automation infrastructure for the team's model development & execution commitments.
Supporting the team's ongoing efforts towards operational resilience through the development of robust automation processes and the promotion of sound programming practices.
Development and implementation of best practices relating to data aggregation, modelling, and stress testing processes.
Driving bespoke solutions for modelling endeavors where available data is limited, noisy, incomplete, or otherwise unfit for use as-is.
Maintain up-to-date documentation on data processing steps and conventions.
Develop & maintain team-wide programming best practices, style guide, and other tools to help drive consistency and reliability of modelling outcomes.
Hands on work with ad-hoc analyses and assessment of data quality.
Lead the preparation of ad hoc analysis for senior leadership.
Deepen our team's understanding and recordkeeping of metadata and qualitative attributes relating to our data sources, including known deficiencies and other details relevant to a data source's suitability for modelling.
Uses sophisticated analytical thought to exercise judgement and identify solutions.
Communicates difficult concepts; converts information to compelling business context and advice; influences and gains alignment across increasingly senior stakeholders.
Must be able to work with minimal supervision in an unstructured and fast-paced environment.
Lead the team's effort to demonstrate the reliability and suitability of modelling data in our ongoing dialogue with model validation.
Maintain good relations with all internal stakeholders and ensure that all their requirements are met.
Monitor/report on compliance, management, and strategic initiatives.
Support established enterprise-wide risk escalation, review and approval processes, data management, policies and risk assessment processes.
Should be able to develop good business relationships with internal partners.
Analytical, problem solving and consensus building skills.
Drive a culture of continuous improvement and efficiency by ensuring efficient and effective processes, leveraging automation where appropriate.
Work is guided by policies and industry standards/methods.
Work in a highly interactive, team-oriented environment with Stakeholders across the enterprise.
Ensure core Bank data and metadata is appropriately managed to support business requirements / needs.
Consistently exercise discretion in managing correspondence, information, and all matters of confidentiality; escalate issues where appropriate.
Must be able to think conceptually (“out-of-the-box”) and have a high degree of attention for detail.
Provides training and mentoring for new and less experienced staff.
Continuously enhance knowledge / expertise in own area and keep current on emerging trends /developments and grow knowledge of the business, analytical tools and techniques.
Prioritize and manage own workload to deliver quality results and meet assigned timelines.
Support a positive work environment that promotes service to the business, quality, innovation, and teamwork and ensure timely communication of issues/ points of interest.
Identify and recommend opportunities to enhance productivity, effectiveness, and operational efficiency.
Establish effective relationships across multiple business and technology partners, program, and project managers.
Participate in knowledge transfer within the team and business units.
Process improvement-focused mindset, with consistent and demonstrated track record of full-scale process re-design and automation.
Proactive and highly motivated individual who will take the initiative and who can work independently and in a team environment.