Director

  • 36893
  • Life - Data Science
  • |
  • Ontario, Canada
  • |
  • Feb 25, 2020
Insurance
RESPONSIBILITIES
  • identify opportunities and develop customer-centric analytical solutions meeting business needs aligned to the business strategy.
  • Demonstrate thought leadership and lead DataOps and MLOps practices that enables proprietary data and predictive models as competitive advantage focusing on solving the business problems in a test and learn environment.
  • Responsible for the Model Governance and acting as an analytics translator to identify high impact business problems and work collaboratively with business functions to embed advanced analytics solutions across Finance, Risk and Operations.
  • Be a subject matter expertise on business processes relates to data and analytics, and coach and mentor team with clear and precise directions to deliver value to the various business functions.
  • Translate complex functional and technical requirements into a thoughtful solution design/architecture to build and deploy analytical applications.
  • Ensure model and data pipelines are scalable and compliant with data and model governance guidelines.
  • Drive accountability via strong delivery-oriented ownership to all the data and advanced analytics initiatives.
  • Work collaboratively with business functions to design, develop, and implement cloud-based data and AI model pipelines.
  • Drive transparency via documentation of data and advanced analytics solutions and democratize deep understanding of data and advanced analytics throughout the team and other business functions.
QUALIFICATIONS
  • Post-graduate degree in Operations Research/Computer science/Finance/Economics/Mathematics/Statistics/Physics or any other data and compute intensive field.
  • Code efficiently and effectively in R, Python, JScript, pySpark, Shell Scripting, SQL. Awareness of C/C++/Java would be value added. Must be proficient in Linux OS.
  • Solid working knowledge of productionizing ML/DL models using open-source libraries is preferred.
  • Solid working knowledge of analytical deployment frontend/backend tools is preferred.
  • 5-7 years of progressive experience in data architecture, data modeling, data pipelining, serverless computing and parallel processing to build robust real-time and batch data pipelines.
  • Experience in design thinking and agile prototyping to develop and test business use cases and analytical applications.
  • Strong communication skills to articulate complex problems and demonstrate thought leadership in developing and delivering solutions to stakeholders.
  • Demonstrated ability to build strong relationship with business partners and influence key decision makers.
  • 5-7 years of progressive management experience leading a team of modelling professionals.
  • Strong appetite to learn the business and passionate about solving business problems.
  • Strong appetite to self-learn advanced analytics tools/techniques, and open to share knowledge with others.