Responsibilities
- Lead the framing, development, and deployment at the scale of machine learning models.
- Understand the risk of various classes of businesses.
- Turn vast amounts of structured and unstructured data from many sources (web data, geolocation, satellite imaging, etc.) into novel insights about behavior and risk.
- Drive the project’s direction and maintain focus.
- Work closely with Product Management and Software Engineers.
Requirements
- 5+ years of experience in engineering and data science.
- In-depth understanding of applied machine learning algorithms, especially NLP, and statistics.
- Experience in Python and its major data science libraries, and have deployed models and algorithms in production.
- Comfortable with data science as well as with the engineering required to bring your models to production.
- Excited about using a wide set of technologies, ultimately focused on finding the right tool for the job.
- Value open, frank, and respectful communication.
Nice to Have
- Experience with AWS.
- Hands-on experience with data analytics and data engineering.
Benefits
- Significant equity options package.
- Work with an ambitious, smart, global, and fun team to transform a $1T global industry.
- 20 days of PTO a year.
- Global team offsites.
- Phone reimbursement.
- Gym reimbursement.
- Student stipend.
Work Arrangement
Remote (Worldwide)
Additional Information
- The salary range listed is an estimate and will vary based on a variety of factors. Final compensation will be determined during the offer stage based on relevant experience, performance during the interview process, and geographic location, and may therefore differ from the posted range.
