Think insurance is boring? We did too. So we built a company that takes everything you think you know about buying insurance and turns it on its head.
At Cover, we want to become the largest and most customer centric insurance company in the world.
Founded in 2016, Cover is a mobile-first insurance platform licensed in all 50 states, working with over 35 carriers and underwriting our own insurance products. We were part of Y Combinator’s W16 batch, and have gone on to raise $37 million across three funding rounds backed by world class investors.
We’re growing fast. In the past year we’ve scaled the team across our San Francisco and Toronto offices. Across our diverse and multi-skilled team we’re working together to deliver a service that’s effortless to interact with, transparently priced, and built on a sustainable and long term footing.
We’re pushing hard to make our vision of insurance a reality and we want dedicated, inquisitive and collaborative people who are ready to play their part in achieving our goal.
Are you a machine learning engineer who:·
-Considers yourself to be a full-stack data scientist?
-Routinely tries algorithms that you read about on paperswithcode (or similar)?
-Revisits projects on a regular basis to look for opportunities for improvement?
-Is happy when a process is fully automated?
The Research and Development team at Cover is growing and is looking for a machine learning engineer to help us build exciting, new insurance products that will help propel our growth to new heights. We’re in search of team members who are constantly looking for ways to improve upon ‘the way things have always been done’ and who make those visions reality - people who accelerate our velocity through code, statistics, machine learning, and new insights. In this job, you will be identifying risk traits from image and/or video data to simultaneously bring transparency and greater predictiveness to our risk models.
What you’ll be doing everyday:
- Take ownership of ML projects by:
- Acquiring data including any necessary labels,
- Selection and training of neural networks
- Deployment of ML as a service
- Development of interetability features
- Proactively identifying and researching new opportunities for applications of machine learning to insurance problems
- Develop and mentor other team members on machine learning.
What you bring to the table:
- 4-8 years experience in machine learning, including computer vision use cases.
- A degree in mathematics, statistics, computer science, physics or another quantitative discipline.
- Master’s degree or successful completion of multiple data science projects such as Kaggle competitions.
- Experience with at least one cloud platform and their data science tools (for example, AWS, Sagemaker, AWS pretrained and/or ML services, etc)
- Experience with data labeling services such as MTurk, Figure Eight, Labelbox, or Scale AI.
- Solid communication skills
What we Offer:
- The opportunity to work remote anywhere in North America industry leaders to be at the forefront of innovation in insurtech
- Stock options to give you a stake in the long term success of the company
- Unlimited vacations to always put your wellness first
- Opportunity to take ownership on key initiatives and carve out the career path that you desire
We Believe in Equal Opportunity
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, colour, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.