About GreyNoise
GreyNoise is a mission driven security startup focused on helping organizations understand and mitigate risks from Internet scanning and exploitation. GreyNoise provides real-time intelligence on all actors scanning the Internet and how some of them are attempting to exploit vulnerabilities on assets connected to corporate networks. The intelligence is highly trusted because it’s generated from a global fleet of thousands of purpose built sensors observing the Internet. Advanced data science techniques and AI are used to process millions of observed events into real-time intelligence for customers.Organizations use GreyNoise intelligence to understand the background scanning noise on the Internet and reduce up to 40% of alerts in a SOC.
Threat hunting, vulnerability prioritization, incident investigation, and emerging threat response are other popular use cases for GreyNoise. The user base includes more than 10,000 community users and with 100 plus paid customers.All positions are fully remote within the US, with optional office attendance at our DC area headquarters, unless otherwise specified. Applicants must have US work authorization.
The Role
We are seeking a passionate Data Scientist with a strong background in AI and Machine Learning to join our innovative team. In this role, you will delve deep into the vast datasets collected from our global internet honeypot sensor network. Your mission is to design and implement advanced machine learning models that automatically detect anomalies, uncover hidden patterns, and predict emerging threats in real-time internet traffic. By leveraging cutting-edge AI/ML techniques, including the latest in Large Language Models (LLMs), you will help us interpret complex internet activity, enhancing our product features and delivering actionable insights to our customers.
Collaborating closely with cross-functional teams, your work will directly contribute to making the internet a safer place.
What You Will Do
Work closely with Engineering, Research, and Product Development teams to:
- Develop and deploy machine learning models for real-time anomaly detection and threat identification.
- Automate the discovery of interesting and anomalous data from our global honeypot network.
- Research and implement new LLM technologies to help "read and understand" complex internet traffic patterns.
- Integrate new visualizations and statistical models into our product to enhance user experience and data interpretation.
- Ensure data quality by collaborating with infrastructure engineers to develop tests and alerts for detecting defects and determining their origin.
- Optimize data pipelines in collaboration with data engineers for efficient data processing.
- Interface directly with customers to capture analytical requests and translate them into actionable engineering requirements.
- Present findings through social media, blogs, and conferences to engage with the broader community.
- Stay current with the latest AI/ML research and cybersecurity trends to continuously improve our solutions.
- Monitor and tune ML models in production environments to ensure scalability and reliability.
What You Will Bring
- 5+ years of data science experience and/or an advanced degree in a relevant discipline (Data Science, Machine Learning, Operations Research, etc.).
- Experience implementing machine learning techniques with real-world data, preferably in computer networking or cybersecurity; specifically clustering and anomaly detection.
- Proficiency with machine learning frameworks and libraries such as PyTorch, scikit-learn, and numpy.
- Experience with natural language processing (NLP) techniques and working with LLMs.
- Strong programming skills in Python and familiarity with statistical analysis.
- Experience in data visualization with a variety of tools and working with front-end developers to bring visualizations to production.
- Familiarity with database and big data technologies (Elasticsearch, SQL, Snowflake, etc.).
- Knowledge of cloud-based hosting and ML services, particularly AWS.
- Understanding of containerization and deployment technologies like Docker and Kubernetes.
- Ability to communicate technical concepts effectively, both to teammates and external audiences.
- Excellent problem-solving skills and adaptability in a dynamic environment.
Nice to Haves
- 2+ years of experience in the cybersecurity industry or relevant training.
- Experience developing prototypes using AWS or other cloud providers.
- Basic understanding of information security and networking topics, such as internet protocols (e.g., HTTP, SSH, Telnet), remote service exploitation, Denial-of-Service attacks, and PCAP data.
A Few of our Data Science Principles
- Analysis and models are most useful when they are explainable.
- Data Science is an enabler of other teams.
- Design research projects with implementation in mind.
- Write tests, readable code, and documentation out of respect for your colleagues.
- Data doesn’t change but how we see it does.
Benefits
💵 Equity in a high-growth, Series-A startup👩⚕️ 100% covered health, dental, vision, and life plans for all employees6️⃣ Competitive 401k employer match of 6%, which is special for a startup. This will be 100% matched and vested from day 1🏖 Unlimited paid time off. To encourage time off from work and ensure overall employee health and wellness, GreyNoise strongly recommends each employee to take at least 120 hours of PTO (3 weeks) annually, including at least five consecutive business days🌎 Remote-first culture.
While we are headquartered in the Washington DC area, we have a distributed workforce -- with the majority of our team working remotely from across the country💻 Equipment budget. Every new employee gets $3,000 to spend on equipment, so you can pick whatever works best for you👼 Paid family leave for all employees. We offer 4 months of paid leave (birth or adoption), plus 2 months of optional unpaid leave, so new parents have time to adjust to the new life (and work) schedule📚 Learning & development budget. All employees receive an annual $1,500 towards professional development related to their job function. The stipend can be applied to tuition, books, conferences, and more🌴 Company offsites and monthly local hangouts to encourage team bonding
GreyNoise Culture
The hallmark of any great company is a palpable and viscous culture. The most important pillars of our culture are:
- Be transparent, honest, and objective. This is what it means to be “clinical”
- Empathize with customers, partners, and each other
- Learn from mistakes and share the knowledge
- The way feedback is delivered to one another matters as much as the feedback itself
- Good work-life balance is the key to sustained productivity
- The measure of a team member’s effectiveness is how well the rest of the team operates in their unexpected absence
- No such thing as a million dollar idea, only million dollar execution
- Out-innovate our previous selves
Check out our (work-in-progress)
longform culture document.
Explainability
Any security product that is a “black box” that asks you to blindly trust it should raise red flags - we believe the same is true of your place of work. We obviously think GreyNoise is doing something unique, but don’t take our word for it - ask any of our 150+ enterprise customers, investors, thousands of happy users, or dozens of journalists who have cited GreyNoise over the past few years.
Why You Should Work at GreyNoise
- You enjoy identifying and solving hard problems
- You are comfortable taking an idea from concept to customer
- You are open to both explaining your stance and questioning others in a clinical, open-minded, and respectful manner
- You want to directly impact users
- You want to grow beyond your current skill set
Apply for the job
Do you want to join our team? Then we'd love to hear about you!
