Senior AI/ML Engineer (On-Site)

Who is Cover Whale?

Cover Whale improves road safety by combining the insurance products we sell with our data-driven driver coaching and safety program. Our safety program is proven to save lives while delivering better insurance for our drivers.

We provide easy insurance options for our drivers at industry-leading insurance loss ratios for the insurance companies that support Cover Whale. The Commercial Auto and Trucking segment of the insurance industry badly needs our help and so do the hard-working drivers who have been struggling with ever-increasing insurance costs year after year. Join us in the mission!

Founded in 2019, Cover Whale recently closed under a $16M seed funding round (the largest InsurTech seed round raised in North America) and is scaling rapidly. For more information, please visit www.coverwhale.com

The Role

As a Senior AI/ML Engineer for Cover Whale, you will focus on building AI/ML algorithms. You will partner with data engineering, data science, product, business, UX, engineering, and operations. You will need to be a self-starter with a bias for action and excellent communication skills. This is a rare opportunity, moving at the speed of a start-up, with the backing and in-house data of a traditional insurance company. You will bridge the art of what’s possible across today’s rapidly evolving commercial insurance landscape.

Please note: This is an on-site role with the requirement to be in the office at least 4 times per week.

Responsibilities:

• Build prototype AI/ ML models and tools to help us understand our customers and create personalized customer recommendations across multiple use cases and productize solutions to scale
• Deeply understand customers, their behaviors and pain points, and develop a diversity of AI models addressing an array of customers’ needs
• Translate business needs into AI/ML problems and create innovative solutions to advance our business goals
• Determine the types and amount of data needed and work with the data engineer to identify data sources and ingest them into data lake
• Structure, standardize, and annotate data into processable formats for ML; enrich data with necessary attributes to allow sophisticated personalization
• Help shape the way our data science team does work - researching and making key decisions about what we build, how we build it, and which tools are best for solving our problems
• Work alongside software and data engineers to implement data processing and visualization systems that make data readily available and simplify how insights are communicated
• Evaluate the performance of AI models and make tradeoffs against quality metrics
• Investigate, and resolve performance issues in a timely manner

Requirements

• Master’s degree in Mathematics, ML, Statistics, Computer Science, Software/Data Engineering, or a related field
• 5+ years with Python
• 2+ years of experience leading a team of data scientists.
• Expertise in at least one popular Python data science/ml framework (pandas and pytorch preferred)
• Experience with microservices architectures (and ideally experience with Kubernetes)
• Strong mathematical background in probability, statistics, and optimization algorithms.
• 2-3 years experience with AWS Sagemaker.
• Experience in building machine learning models and deploying them to production to make real decisions, then measuring the impact of these decisions.
• Deep understanding of and have applied various machine learning techniques for solving real-world problems.
• Proficient with SQL and can work “full stack” to integrate solutions with our data ecosystem
• Any experience with big data formats such as arrow, parquet, or similar
• Experience with natural language processing (NLP) and computer vision is a plus
• Confident in taking ownership of projects from start to finish and enjoy the process of turning nebulous ideas into reality
• Excellent communication skills
• A self-starter who drives projects and builds strong relationships with stakeholders and teams to tackle large cross-functional efforts
• Thrive with minimal guidance and process
• Worked in both small teams/incubators and large corporations

The Expected base pay for the role will be between $147,000-$160,000 per year at the commencement of employment. However, base pay if hired will be determined on an individualized basis and is only part of the total compensation package, which, de