About CyberCube:
🟩 The market leader in digital analytics 📊 with the mission of delivering the world’s leading cyber risk analytics 🌐 on one of the most critical risks of today and the future.
🟩 Exceptionally well-funded startup 💰 that has raised over $100MM from top-tier investors.
🟩 Explosive team growth 🚀 (from 15 employees in SF to 100+ globally 🌍).
🟩 Used by 75% of the top 40 US and European cyber insurance carriers & surpassing 100 clients in 2023 with a >99% retention rate.
🟩 CyberCube and its products win industry awards 🏆 every year. (eg. Cyber Risk Solution of the Year & InsurTech Product of the Year). We were recognized with 17 awards in 2023.
🟩 Senior leadership is committed to attracting, developing, and exciting exceptional people from diverse backgrounds and enabling them to work collaboratively across disciplines to do the best work of their careers.
🟩 At CyberCube, we drive ownership for excellence, empowering our team to take initiative, deliver results, and continually raise the bar.
🟩 Named on Forbes’ America’s Best Startup Employers list three years in a row (2021, 2022, 2023)! 🎖️
🟩 Learn what it’s like to be part of CyberCube’s mission: Watch this leadership team interview!🎥
Are you passionate about shaping the future of cybersecurity and risk management? As a Cyber Risk and Analytics Engineer you’ll play a critical role in our Analytics team, working alongside industry-leading experts to develop innovative cyber risk models that drive decision-making in the insurance industry.
Join us to dive deep into cybersecurity data, analyze the latest cyber threats, and craft models that assess risks for businesses worldwide. Collaborate with talented teams across Data Science, Engineering, and Product Development, contributing to solutions that quantify cyber risk from growing cyber threats like ransomware, data breaches, and critical vulnerabilities.
Imagine combining your technical skills in Python, SQL, big data frameworks like Spark/Hadoop, and knowledge of the cyber landscape to create cutting-edge risk scoring models that influence an entire industry. This role is ideal for someone with a strong analytical mindset and a passion for cybersecurity and risk management. You’ll have the opportunity to research, innovate, and provide expert insights that shape product development and impact real-world cybersecurity decisions.
Ready to make a difference in the cybersecurity field? If you’re driven by curiosity, eager to learn, and excited to work in an agile environment, we want you on our team! Apply now and take the next step in your career as a Cyber Risk and Analytics Engineer.
Responsibilities
- Evaluate data sources and develop use cases for cyber risk metrics.
- Build and validate cyber risk models for the insurance industry.
- Conduct research on emerging cybersecurity threats and trends.
- Collaborate with cross-functional teams to implement risk models.
- Communicate insights and educate internal and external stakeholders.
Skills & Qualifications
- Proficiency in Python / R, SQL, big data frameworks and APIs.
- Experience in cybersecurity, data science, or risk modeling.
- Strong problem-solving, communication, and presentation skills.
- Eagerness to learn, adapt, and contribute in an agile work environment.
Why You'll Love It Here:
- Play an instrumental role in reshaping one of the oldest industries in the world
- Competitive salary and meaningful early stage equity
- Company paid learning and development assistance
- Meaningful equity
- Vision and dental coverage
- Fully stocked kitchen
- Extra vacation days during winter holidays
- Flexible working hours and the option to work from home when necessary
- Company supported mentorship program
- Grow in a collaborative, respectful, and empathetic culture
#LI-HYBRID
CyberCube Analytics, Inc. is an equal opportunity employer. We don’t tolerate discrimination against age, gender, gender identity, gender expression, sexual orientation, race, color, nationality, ethnicity, religion, disability, veteran status, protected genetic information or political affiliation.
