Sr Mgr, Analytics & Insights Job Description

Sr Mgr, Analytics & Insights Job Description Template

Our company is looking for a Sr Mgr, Analytics & Insights to join our team.

Responsibilities:

  • Train and guide the analytics team to design and execute suitable analytical solutions in a timely fashion to support business decisions;
  • Liaise with business stakeholders to ensure timely and accurate deliverables;
  • Foster an environment and culture that encourages productivity, innovation, process improvement, teamwork, and a high level of professionalism;
  • Lead the effort in identifying and applying various analytics solutions to support Wealth data & analytics transformation agenda.

Requirements:

  • At least 5+ years of relevant experience in data, analytics and business insights in the Financial Services industry;
  • Experienced people leader with demonstrated experience in identifying and growing talent;
  • Disciplined with a proven track record of delivering results and executing with excellence;
  • Detail oriented with excellent organization skills and ability to effectively manage work under tight timelines and changing priorities;
  • Superior communication skills with proven ability to communicate quantitative/ qualitative information and key messages in a clear and compelling way;
  • Understand and experienced in modern analytical solutions, e.g. machine learning, open source analytical tools, distributional processing system;
  • Comfortable leading through transformational change and recognized as a champion for continuous improvement;
  • Experience in Consulting service or Wealth/Asset Management is considered an asset;
  • Ten (10) or more years relevant experience;
  • Experience in Tableau and other visualization tools is considered an asset;
  • Experience in distributional processing environment (e.g. Hadoop) is an asset;
  • Experienced and skilled with various analytics methodologies, such as PCA, clustering, classification tree, Regression, Gradient Boosting;
  • Experienced with data engineering practice and data warehouse;
  • Undergraduate degree or technical certificate;
  • Experienced and skilled with various tools for data wrangling/manipulation, statistical analysis, modeling, such as SAS, Python, R, PySpark, HIVE.