Quantitative Researcher

About the company

Our client is a cybersecurity company.

The role

Raydar is recruiting for this role on behalf of our client. Design and refine statistical and machine learning models that flag suspicious behavior as it happens. You will carry research from raw, unconventional data all the way into live systems, with ownership of specific modeling goals and their results.

What you'll do

• Create new predictive models and strengthen existing ones so that malicious activity is identified with very high accuracy.
• Investigate incidents by separating hostile behavior from ordinary user behavior across long activity histories.
• Handle the research lifecycle yourself, from collecting and tidying data to crafting model inputs and fitting models.
• Weigh response-time needs when choosing a modeling approach, then deploy and look after the code you write.
• Work closely with a small group of researchers and engineers, accountable for defined modeling targets.

What we're looking for

• A background in quantitative research at a leading proprietary trading firm or investment fund.
• Solid grounding in applied mathematics and statistical methods, including outlier detection, user behavior modeling and language processing.
• A record of carrying machine learning projects from data gathering through to production release on your own.
• Fluency in at least one of Python, C++ or Rust, plus day-to-day comfort with Git.
• Hands-on experience taking models from training into live use, with attention to data preparation and speed requirements.
• A bachelor's degree or higher in a quantitative discipline such as computer science, statistics or mathematics from a strong US university.
• Existing authorization to work in the US.

Bonus points

• Familiarity with unconventional data sources in financial markets.
• Comfort working with relational databases and efficient querying.
• A graduate degree from a well-regarded institution.

Benefits

• Health, dental and vision coverage

Location and work model

• San Francisco, CA, United States
• On-site, 5 days per week in office
• Full-time

Compensation, as the posting describes it

• Equity
• Retirement plan
• Commission