Senior Data Scientist

  • 36139
  • Life - Data Science
  • |
  • Ontario, Canada
  • |
  • Oct 28, 2019
Insurance
RESPONSIBILITIES
  • Takes a leading role in the model validation in Group Advanced Analytics by developing the model validation and risk management framework.
  • Reviews documentation, meets with the business, model owner to ensure understanding of the business problem.
  • Assesses the data for model development, checks assumptions, inputs to the model and does in-depth analysis to identify potential issues.
  • Independently develops benchmark model to assess whether submitted model behaviour is consistent with the documented specifications and intended use.
  • Compares validation results with model developer results for replicability.
  • Ensure the transparency and interpretability of the models by keeping current with new research and methodologies that can explain black box models.
  • Ensure that proper and adequate model documentation and model risk mitigation processes are in place in order to appropriately assess and mitigate model risk.
  • Keeps informed of current practices and research in statistical and machine learning modelling techniques and risk management by reading academic literature, attending academic and practitioner workshops and conferences.
  • Provides technical advice and guidance to assigned business/group on implementation of the model validation framework, and resolution of model risk issues.
  • Develops and maintains in-depth knowledge of business and related model validation/risk management requirements and regulatory guidelines.
  • Builds effective relationships with internal/external partners.
  • Ensures that business units understand that the model submission process involves preparing adequate model documentation to enable an appropriate model review.
  • Participate in ad-hoc projects.
  • Implement measurement & documentation framework against all project work.
  • Generate insights in such a way that the businesses can clearly understand the quantifiable value. Enable the business to make clear trade-offs between and among choices, with a reasonable view into the most likely outcomes of each.
  • Turn statistical and computational analysis into user-friendly graphs, charts, and animation. Enable those who aren’t professional data analysts to effectively interpret data. Ability to communicate results and educate others through reports and presentations.
  • Provide thought leadership around analytics methodology, tools, and measurement.
QUALIFICATIONS
  • Advanced degree in Statistics, Math, Comp Sci, Engineering or other related discipline.
  • Minimum of 5 years' experience specifically in building statistical/ machine learning models, data analysis and data mining.
  • Experience with model risk management practices, model life cycle.
  • In-depth knowledge & experience with risk policy frameworks; quality control / testing frameworks.
  • Experience with Natural Language Processing, unstructured data, use of APIs.
  • Proficient in either Python, R, SAS, SQL with working knowledge of the others.
  • Demonstrated data transformation & manipulation experience.
  • Track record of delivering innovative analytical insights to lines of businesses.
  • Model validation experience is preferred.
  • Experience with Big Data platforms.
  • Experience with Gitlab.
  • Strong commitment to organizational success and team work.
  • Adaptable and open to change with strong collaboration and communication skills.
  • Insurance/Financial Services experience desired.
  • Inspires and motivates others.
  • Role model of ethics and integrity who builds a culture of respect.
  • Highly effective change agent who embraces change and leads change management.
  • Provides courageous advice.
  • Results oriented; highly focused on accountability.
  • Ability to handle multiple partners.
  • Demonstrates a commitment to delivering excellent service balanced with appropriate risk management.
  • Strategic perspective.
  • Highly collaborative working style.