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Data Scientist

Toronto, Ontario · Computer/Software

Data Scientist

About the role

This is your chance to join a fast-track insurtech venture on a mission to take the commercial (re)insurance placement workflow into the 21st century and beyond.
As the founding member of our data science team you will be working closely with the product and engineering teams to identify and develop high value data-driven product features, e.g. price recommendation, business intelligence models, etc. Being a vital member of the product and engineering teams, you will also leverage an analytical and data science approach to guide measurement, strategy and tactical decision making as we continue to grow and evolve our product. As the data we capture during the (re)insurance placement process has increased we’ve identified several possible opportunities where we can apply machine learning techniques to make it easier and faster for our customers to place (re)insurance.

About the Company

Building the next generation of technology for the Commercial Lines insurance and reinsurance markets, we work with forward-looking brokerages to deliver increased volumes, higher commissions and maximal efficiency.

Our Company Culture

We promote a highly progressive environment to allow our teammates to reach their full potential. Our innovative culture is anchored in four pillars: inclusion, empathy, customer excellence, and agility.
We offer a “work from anywhere, anytime you prefer” policy, along with competitive compensation packages including benefits, stock options and commissions.
Additionally, we offer digital team-building events, on-demand remote-work locations, team gatherings in attractive locations (post-covid), and we support our team’s aspirations, whether they overlap with our commercial objectives or less so.

What you'll do

Research and Strategy

  • Establishing our data science and machine learning approach within the company

  • Identify opportunities to add value through data science and analytics

  • Validate existing theories for our recommendations engine

  • Rigorous use of statistical modelling to support decision making Technical Implementation

  • Introduction of machine learning frameworks such as scikit-learn, Tensorflow, or other framework of your choosing

  • Identification, implementation, evaluation of recommendation and other data science models

  • Productionalizing machine learning models with the entire engineering team

  • Support the product, sales and engineering teams with insights gained from analyzing company data.

  • Working with our SQL based DB and accompanying analytics data

What we look for

  • Encouraging a culture of experimentation and scientific rigour in the organization

  • A proven ability to drive business results from data-based insights

  • Pragmatism; being committed to getting things done while understanding tradeoffs

  • Fast learner, comfortable with learning (re)insurance lingo and technical concepts;

  • A drive to get better every day, demonstrated by evident career progression and explorations;

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