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Head of Advanced Analytics At Brookfield Asset Management

Location: Toronto, Ontario

Job Description

Brookfield Asset Management
Brookfield Asset Management Inc. (“Brookfield”) is a global alternative asset manager with over $285 billion in assets under management. Brookfield has over a 100-year history of owning and operating assets with a focus on property, renewable power, infrastructure and private equity. Brookfield offers a range of public and private investment products and services, which leverage their expertise and experience and provide a distinct competitive advantage in the markets in which they operate. Brookfield is co-listed on the New York and Toronto Stock Exchanges under the symbols BAM and BAM.A, respectively, and on the NYSE Euronext under the symbol BAMA. For more information, please visit our web site at

Private Equity Group

Brookfield Asset Management’s Private Equity Group is forming a new Advanced Analytics group and is seeking a recognized expert in data science to build internal capability in this area. Specifically, the Head of Advanced Analytics will identify business challenges, uncover facts, design innovative algorithms, create scale through creating tools and repeatable solutions (models, processes, etc.) and provide support to colleagues to achieve the maximum benefit from incorporating advanced analytics.

Reporting to the Managing Partner, Business Operations, the Head of Advanced Analytics will be an experienced analytics professional who is adept and explaining insights and developing plans for action. S/he will be responsible for delivering business impact Brookfield’s private equity group portfolio companies and assisting with diligence on new acquisition opportunities by building and deploying advanced analytics solutions.



  • Deploy all aspects of advanced analytics from discovery through to operationalization to improve core functions, including, but not limited to: customer acquisition, pricing, servicing and retention, product development, network planning and maintenance
  • Build an advanced analytics practice including: data discovery, data engineering and quality assurance, data modelling, analysis and insight assessment, business communication and technology solution development and deployment.
  • Develop long term plan for the Advanced Analytics practice, including key focus areas, budget, talent attraction, technological platform and interaction model with the rest of the organization
  • Initiate and own major PE-wide analytics initiatives from an analytics and technological standpoint
  • Define and develop internal support and utilization model, balancing external resources with building out a team
  • Attract and develop talent – data scientists, engineers and platform and application specialists
  • Manage team on day-to-day basis, providing guidance and feedback as they deliver analytical solutions
  • Manage arrangements with 3rd party data and analytics providers

Planning and execution

  • Develop plan and utilization approach for Advanced Analytics, manage execution and measure results
  • Coordinate and prioritize use cases / focus areas for the application of advanced analytics
  • Ensure analytical insights and products are embedded into business processes
  • Manage Big Data infrastructure
  • Manage advanced analytics budget

Required skills and Qualifications

  • Significant relevant experience building and deploying advanced analytics solutions in B2C and B2B environments. Relevant topics include: social media analysis, customer acquisition, customer segmentation and targeting, customer LTV maximization, churn prevention, cost modeling of transportation & logistics operations, predictive maintenance
  • 7+ years of work experience in advanced analytics
  • PhD or advanced degree required in a field linked to business analytics, statistics, operations research, applied mathematics, computer science, engineering, or related field
  • Deep technical and data science expertise, including experience in the following:
  • Analytical methods: statistical modeling (e.g., linear regression, GLMs, time series), supervised machine learning (e.g., random forests, neural networks), design of experiments, segmentation/clustering, text mining, network analysis (e.g., location allocation), optimization, simulation
  • Analytics tools: Data wrangling (SQL, R, Python, PostGRESql) Data Modeling (R, Python, SAS, RapidMiner, SPSS), Data visualization (Tableau, Microstrategy)
  • Big Data environments: AWS, Spark, Hadoop, Azure
  • Experience building in-production models, including associated scripting, error handling and documentation
  • Experience using analytics to drive business outcomes
  • Proven ability to drive P&L impact through analytics
  • Demonstrated ability to present analytical results and recommendations in simple business language, verbally and in writing.
  • Demonstrated ability to lead and manage projects and teams

Work Location

Toronto with Global accountability, supporting diverse businesses in multiple geographies.

Approximately 30% travel.