Staff Machine Learning Engineer

If you’re good at what you do, you can work anywhere. If you’re the best at what you do, come work for Doma.

Want to infuse a $34B sector of the insurance and real estate industry with predictive analytics and a tech-forward customer experience? Join Doma and send an entirely new type of real estate model into the world.

About Us  

Doma offers solutions for lenders, real estate professionals, title agents, and homeowners that make closings vastly simpler and more efficient, reducing cost and increasing customer satisfaction.

Our Values

• People First - We communicate with honesty and respect to our customers, colleagues, and partners.
• Better Together - We believe diversity, equity and inclusion creates value through the differences in our backgrounds, experiences, and perspectives.
• Solution Driven - We encourage calculated risk-taking, and we know that some of our best learning happens by making mistakes along the way.
• Act with Integrity - We hold ourselves to the highest ethical standards in all of our business practices.

What you’ll be working on: 

• We build machine learning models end-to-end. You will take full ownership of one of our core revenue-generating risk and underwriting models. This will involve any and all of the following workstreams:
• Data collection
• Data pipelines
• Retraining and optimization
• Evaluation
• Inference and serving
• Monitoring and quality assurance
• Other related dev tooling and infrastructure work
• You will conduct ad-hoc analyses, tests and retrospectives on questions related to our models, for delivery to internal stakeholders and external partners/clients
• You will serve as a go-to expert in title risk and underwriting for our team and the company. This includes exploring ways to reduce model losses, improve the fidelity of our projected losses, and identify new risks in our domain 
• You will deliver new data science products targeting unexplored areas of the title and escrow workflow, from their inception to their deployment as machine learning models  

Required Qualifications: 

• 5+ years of professional experience in data science or machine learning engineering 
• Strong background in statistics, computer science, machine learning, operations research, or mathematics
• Experience developing and deploying models end to end in a production environment, with proficiency in Python, SQL, Git, Docker
• Experience with object-oriented programming and software engineering practices, such as version control, unit …