Machine Learning Engineer (Remote Friendly)
Remote
Applications have closed
Vouch, Inc.
Vouch is a new kind of digital insurer that protects startups from mistakes, litigation and attack.About Vouch:
Insurance... sounds slow, old-fashioned, and unexciting. Exactly. Insurance is broken, and it's failing fast-moving, innovative startups.
Vouch is a new, technology-first insurance company backed with $160M in funding from world-class investors. Like Stripe for payments or Brex for credit cards, Vouch is creating the go-to business insurance for high-growth companies.
We're doing this by making insurance fast, responsive, and focused on our customers -high growth and innovative companies. Instead of printed PDF applications and week-long waits, Vouch is building new technology to solve real problems, writing policies that actually cover relevant startup scenarios, and designing simple experiences in an otherwise frustrating industry.
What does the work environment look like at Vouch?
Vouch is a Virtual First Workplace with office locations in SF, Chicago, and NYC . This role can be based anywhere in the U.S as long as you can work our Vouch core collaboration hours (8:30 am-2:30 pm Pacific Time.)
The Job:
Would you like to play a critical role in the success of the next wave of world-changing startups? Are you excited about understanding the pace and evolution of the venture ecosystem? Would you like to contribute to a product that will redefine the risks founders can comfortably take on as they build from ideas into companies? Our mission at Vouch is to craft the best insurance for those building the future, and our Data Team is growing!
Vouch is looking for a Machine Learning Engineer to join our team. As the first hire in this sub-team, you'll start as a generalist and have the opportunity to specialize over time, setting the foundation as we build out our data science function. We’re looking for someone who lives and breathes data, and who wants to own models end to end, from underlying infrastructure to modeling novel data signals that produce business value. You will have the opportunity to quickly contribute to Vouch’s data assets and help shape fundamental aspects of our data-driven culture, building full-stack NLP and ML models on top of the most comprehensive startup dataset in the world.
You will be responsible for:
- Owning full life-cycle (creation, deployment, iteration) of NLP models to classify companies according to their business characteristics, helping our underwriters better understand startups' insurable risks.
- Working with our sales, marketing, product, and insurance teams to evaluate data quality in our core knowledge graph to improve our representation of the venture ecosystem
- Developing graph algorithms for link prediction, node clustering, or entity resolution
- Designing and implementing processes to generate ground truth labeled data sets to validate our models
- Researching and explore innovative ML strategies to operationalize the use of proprietary data in scoring current and potential clients along different risk exposures
- Establishing engineering best practices and methodologies to ensure data transformations and computations are accurate, efficient, and tested.
- Working cross functionally with team members across the Vouch organization to understand the downstream impact of our data models
- Effectively talking (and listening) to engineers, designers, marketers, executives, and other stakeholders. You will not just fit models but will be held accountable for creating business value
About you:
- 3+ years of experience developing, deploying and maintaining high performing, resilient, and real time machine learning systems
- Familiar with the fundamentals of Machine Learning and Statistical Modeling
- Deep knowledge of the Python standard library and data wrangling tools like Pandas
- Familiarity with data science frameworks such as Scikit-Learn, NLTK, NetworkX, PyMC, Keras, etc.
- Have experience with relational data modeling and SQL, including solid knowledge of various datastores and their tradeoffs (RDBMS’s, NoSQL, etc)
- Proficiency working within a shared code base using git and command line tools
- Scrappy, unafraid of digging through raw and messy data
- Pragmatic, not letting the perfect be the enemy of the good
- Most candidates will have a BS, MS or PhD in Computer Science, Engineering, Statistics, Economics, Mathematics, Operations Research, or a related technical field. Surprise us!
Nice to Have:
- Working knowledge of graph databases, SPARQL, rdflib, pyshacl, etc.
- Experience with Airflow, Oozie or other task orchestration/scheduling engines
- Experience with data transformation tooling such as dbt
- Experience with Docker and other packaging and virtualization software
- A background in insurance or other regulated categories
Vouch provides a number of benefits to help you bring your best self to work:
- Competitive compensation and equity packages
- Health, dental, and vision insurance
- Parental leave
- Flexible vacation time (Unlimited PTO)
- Wellness allowance ($80/month)
- Technology allowance ($100/month)
- Monthly Doordash credits ($80/month)
Vouch believes in putting our people first and building a diverse team is at the front of everything that we do. We welcome people from different backgrounds, experiences, and perspectives. We are an equal opportunity employer and celebrate the diversity of our growing team.
If you require reasonable accommodation in completing this application, interviewing, completing any pre-employment testing, or otherwise participating in the employee selection process, please direct your inquiries to recruiting@vouch.us.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Airflow Computer Science Docker Economics Engineering Git Keras Machine Learning Mathematics ML models NLP NLTK NoSQL Oozie Pandas PhD Python RDBMS Research Scikit-learn SQL Statistical modeling Statistics Testing
Perks/benefits: Career development Competitive pay Equity Flex hours Flex vacation Health care Parental leave Startup environment Unlimited paid time off Wellness
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