Data Insight Analytics Manager

Full time @Bank of Montreal posted 12 months ago in Artificial Intelligence & Machine Learning , in Data Science Engineering , in Risk Management Governance & Compliance Email Job

Job Description

Job Family Group:

Data Analytics & Reporting

The Data Analytics Manager, Customer Value Analytics will play a critical contributory role in the North American Data and Analytics Centre of Excellence. This role will oversee the creation of analytical tools, capabilities, and ad-hoc analyses, while making use of a deep understanding of retail banking products and the economics that drive value. This role works collaboratively with partners across Retail Banking, Credit Risk, Finance, Marketing and Technology & Operations and the broader North American Data & Analytics Centre of Excellence team.

  • Integrate information and data into a management framework and create tools to provide recommendations and support business decisions at a strategic and operational level.
  • Provide the data infrastructure to support the planning/forecast, sales, initiatives, reporting, analytics, and revenue growth for both P&C Canada.
  • Work closely with the various groups and leadership teams internally including Product, Finance, T&O, and Risk to develop, evaluate, and provide recommendations on various strategies that affect overall portfolio performance.
  • Will act as the subject matter expert (SME) on both the business side and the data side (Source Systems, ETLs, and automation)

KEY AREAS OF ACCOUNTABILITY

A. Data Management & Analytics

B. Ad-Hoc Analytics

C. Build Analytical Tools and Capabilities

A. Data Management & Analytics

  • Design, develop and maintain code used for data engineering and modelling tasks in order to prepare, manipulate and analyze large internal and external datasets using SAS, R, Python, or SQL.
  • Extract, manipulate and analyze data from a variety of sources to formulate insightful conclusions, provide strategic recommendations, and inform management actions
  • Drive monthly data reconciliation, audits, and investigation into root causes of data discrepancy to ensure data accuracy
  • Collaborate with cross-functional teams to identify opportunities and improve data warehousing needs to meet business demand
  • Will need to understand and be the subject matter expert (SME) on all product and finance source systems and how the team’s ETLs and processes flow for data consumption.

B. Ad-hoc Analytics

  • Perform analyses to identify opportunities, develop insights and recommendations regarding optimizing customers, credit strategy performance, and forecasts across portfolios. Identify and diagnose key business drivers with insights and analytics to help the business move forward.
  • Perform analyses that require the application of financial concepts and tools i.e. NPV, IRR, Discounted Cash Flows, loss projections as well as exposure and risk assessment.
  • Competency in financial modelling, forecasting, business casing, and statistical modelling

C. Build Analytical Tools and Capabilities

  • Create analytical tools and capabilities (i.e. rules based models, dashboards) for internal use to support reports, predictive models, processes, and analytics that will add value and drive the business forward.
  • Establish and maintain both analytical and data model development. Ensure that models are updated, audited, and reconciled with key financials, inputs, and assumptions.
  • Support the delivery and enhancement of regularly scheduled (monthly, quarterly) capabilities for models and/or credit strategic initiatives

KNOWLEDGE AND SKILLS

Knowledge/Role Requirements:

  • 5+ years of experience with data and analytics (Preferably FIs)
  • Bachelor of Applied Science or equivalent – Math, Statistics, Engineering.
  • Previous experience in a finance or risk management environment and exposure to FIs
  • 5+ years of database knowledge
  • Strong technical skills – SAS, SQL, Python, VBA, SQL Server, MS Office Suite, and data visualization tools such as Tableau and Power BI
  • Working knowledge of data management techniques
  • Lending product knowledge is an asset
  • CFA/FRM/CPA designation is an asset but not required

Skills:

  • Strong conceptual and analytical thinking
  • Great communication and interpersonal skills
  • Leadership and collaboration
  • Organizational Understanding
  • Problem-solving
  • Data management and process coordination
  • Prior experience in the banking or financial industry would be an asset

Required skills

Python R SAS SQL VBA

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