Machine Learning Engineer
Clearcover is the smarter car insurance company. We use powerful technology to offer everyday drivers better coverage for less money. We’re proud to be one of the fastest growing startups in Chicago, and we’re currently looking to add a few more extraordinary people to our team.
What is a Machine Learning Engineer?
We are looking for an experienced and motivated Machine Learning Engineer to build the pipelines and productionalize high quality machine learning models. You will be an integral part of our Segmentation and Decision Sciences team that is responsible for identifying and targeting customers with expected positive lifetime value. Our team is built to maximize our individual skill sets and includes you, Data Engineers, Data Analysts, and our Actuaries. Together, we will deliver high value models and tools that will take our business decision making and customer acquisition techniques to the next level.
What will you do?
- Implement production ready machine learning models.
- Develop APIs and/or pub/sub event streams for the purpose inference scoring.
- Build workflows for extracting raw data from our data warehouse/data lake for the purpose of feature engineering.
- Understand policy holder characteristics and insurance product attributes as needed to improve model performance.
- Validate machine learning models via proper train/test techniques.
- Engineer workflows to deliver machine learning powered raw datasets to support data analysis.
- Build model feedback collection processes to enable model optimization and performance reporting.
- Use the scientific method to improve our models, relying on quantitative analysis and experimentation to ensure we’re moving in the right direction.
- Leverage the Python data stack for completing machine learning initiatives.
What do you need?
- At least 2 years of experience as a Machine Learning Engineer, Data Scientist, or in a similar role.
- Significant experience developing production models / pipelines.
- Fluent in Python for data extraction, machine learning, data analysis, reporting, and application development.
- Proficient in SQL for reporting, analysis, and data extraction.
- Familiar with machine learning pipelines leveraging scikit-learn or similar libraries.
- Experience with distributed computing frameworks such as: Dask and/or Spark.
- Ability to leverage notebooks as Data Science artifacts to enable collaboration and pipeline deployment.
- Experience using cloud compute for machine learning tasks with AWS or a similar vendor.
- Ability to communicate and discuss complex topics with technical and non-technical audiences.
- Experience with cloud data warehouses such as Snowflake and/or Redshift
Nice to haves?
- Interest in writing about technical solutions and contributing to open source projects.
- Experience with event streaming for use in Machine Learning workflows (Kafka, Kinesis).
- Familiarity with BI tools such as: Periscope, Tableau, and Looker
- Experience with the AWS Serverless stack for use in Machine Learning workflows (Lambda, API Gateway, SNS, SQS, Kinesis, Step Functions, Fargate, Dynamodb).
- Ability to automate cloud infrastructure provisioning via Terraform and/or Cloudformation.
What's in it for you?
- Unlimited vacation, we hire adults
- Equity for all employees, so you own a piece of the pie too
- Dental and Vision, we've got you covered 100%
- Medical, we cover 90% of your premium, 75% of your dependents and contribute to your HSA and HRA (cha-ching)
- We invest in your future by contributing 3% of your salary to a 401(K), even if you don't
- Come to work pre-taxed through our FSA commuter benefits
- and yes, we have unlimited LaCroix, beer, snacks and the occasional ice cream social