Data Scientist (all offices)
Engineering | San Francisco, CA | Full Time
Coalition was founded by repeat entrepreneurs, Joshua Motta (Cloudflare) and John Hering (Lookout), with a mission to solve cyber risk. We believe that technological risk is among the most pervasive facing society, and we've built the first holistic solution to it by combining free cybersecurity tools to help prevent loss, expert response to mitigate it, and up to $10M of insurance coverage to recover from it. Our technology platform encompasses insurance, threat intelligence, patch and vulnerability scanning, DDoS mitigation, ransomware protection, and more. Coalition’s team of engineers, data scientists, security researchers, incident responders, and insurance personnel protect customers before, during, and after cyber incidents. Our insurance products are backed by Swiss Re, one of the world’s largest (re)insurers, and Argo Group. Our customers are in every industry, and all across the US. We are based in San Francisco, although you'll find some of our team in more exotic places.
If you enjoy solving problems at scale (with lots riding on it) we hope you'll consider joining us.
About the role:
In this role you will work closely with our back-end engineering and information security teams. You can expect to analyze large, sparse datasets across the full spectrum of our signals collection efforts, as well as claims and breach data. You will use these signals to develop predictive analytics, and to improve our underwriting and rating models. You will confront, head-on, numerous computational statistical problems resulting from the large number of heterogenous variables that characterize the technological risk surface and security of an organization, as well as underlying risk dynamics that are constantly changing over time.
- Be(come) an expert on cyber/technological risk, and apply this expertise to make the entire system better.
- Take ownership of our data analysis from helping with data collection and ingestion, to visualizing and interpreting results.
- Create real-world, risk-based models to project cyber loss and prioritize cyber risk remediation based on historical data.
- Work with our security team to address factors not captured by an expected loss model such as serious new vulnerabilities.
- Identify aggregation risks and interventions that could minimize them.
- Investigate new data sources and work with our back-end engineers to improve data collection and to turn your modeling into production-grade code.
- Leverage the large and sparse data sets we collect on technical infrastructure to improve our risk modeling.
- MS or PhD in a quantitative discipline.
- 2 years of relevant work experience in data analysis or related field (e.g., data science, machine learning, financial engineering).
- Experience across the spectrum of decision-making and (business) analytics, with demonstrated ability to utilize the appropriate statistical tools to solve a given data analysis problem.
- Eager to work with messy, real-world datasets from many disparate sources (expect to interface with high-dimensional, sparse data).
- Know how to operate in a modern data science stack - you will have strong SQL skills, experience with data wrangling and script writing, and have familiarity with Python data science tooling.
- See data science as a powerful tool to get things done rather than as an end in itself.
- Passionate about breaking down and understanding complex systems and taking ownership of solving them in a fast-paced and self-starter environment.
- Eager to learn and apply new techniques to a unique data set.
- Information security domain knowledge, ability to understand the nuances of technological vulnerabilities, indicators of risk, and consequence of threats.
- Penetration testing
- Open source intelligence (OSINT)
- Breach database expertise
- Financial engineering / quantitative analyst experience, ability to develop pricing and risk modeling on observed and extrapolated data.
- Python expertise: NumPy/SciPy/pandas, classes & inheritance, list comprehensions, generators, decorators, linting, pytest, pdb.
- Proficient in data visualization using various charting or visual analytic platforms.
- Proficiency in modern ML frameworks (e.g. SparkML, PyTorch, TensorFlow).
- We have lots. Check them out on our site.
- We are a semi-distributed team, with the majority in San Francisco. We prefer that you be in San Francisco, but are open to a team member with demonstrated ability to succeed remotely, especially in the Washington DC Metro Area.
Coalition is proud to be an Equal Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.
Coalition is a security company. A successful background check is required for employment.