Director Data Science

3 weeks ago

Greater Toronto Area Canada, Ontario Adamas Knight Full time

WHO’S THIS WITH?

My client is a global and dynamic Private Equity organization making a significant impact. Joining them means becoming part of one of the most respected and fastest-growing institutional investors globally. With assets exceeding $500 billion and a commitment to the long-term, this organization is set to reach a projected $3 trillion. Boasting a presence in major financial hubs like New York, San Francisco, London, Hong Kong and more, they attract high-calibre individuals from top-tier institutions worldwide.


WHAT’S THE ROLE?

They are looking for a Principal-level data science leader to join an established portfolio value creation team during a transformative period of growth. As part of a team spread across global offices, you will drive value creation across a diverse portfolio of companies. This role involves pre-deal and post-deal involvement, including complex diligences and initiating initiatives to drive EBITA growth at their investments.


WHAT DO I NEED TO BE GOOD AT?

To excel in this role, you must possess strong business judgment, adaptability in fast-paced environments, and the curiosity and courage to tackle challenging problems across various industries. Your problem-solving skills and ability to process complex information will be crucial, along with a collaborative mindset for cross-functionally developing data science products. You will work alongside a team of data science, engineering, product and AI experts and develop models across different use cases, including pricing, forecasting, recommendations or optimization.


WHAT SKILLS DO I NEED?

  • 8+ years of relevant professional experience
  • Degree in statistics, computer science, engineering, mathematics, or equivalent
  • Track record of designing approaches and building statistical models
  • Strong knowledge of Python and SQL, with the ability to translate technical concepts for non-technical stakeholders
  • Proficiency in machine learning for problem-solving across various domains


BENEFITS, PERKS, BONUSES.

  • Accelerated exposure, responsibility, and global career development opportunities
  • The opportunity to contribute to a differentiated data-led and technology-enabled approach to private investing
  • Competitive compensation and comprehensive health and wellness benefits
  • Discretionary bonus can be a significant portion of total compensation (usually exceeding the salary)

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