Data Analyst (Remote, ROU)

​​#WeAreCrowdStrike and our mission is to stop breaches. As a global leader in cybersecurity, our team changed the game. Since our inception, our market leading cloud-native platform has offered unparalleled protection against the most sophisticated cyberattacks. We’re looking for people with limitless passion, a relentless focus on innovation and a fanatical commitment to the customer to join us in shaping the future of cybersecurity. Consistently recognized as a top workplace, CrowdStrike is committed to cultivating an inclusive, remote-first culture that offers people the autonomy and flexibility to balance the needs of work and life while taking their career to the next level. Interested in working for a company that sets the standard and leads with integrity? Join us on a mission that matters - one team, one fight.

About the Role:
CrowdStrike is looking for a Data Analyst to join our growing Generative AI Research Center. This is a junior/entry-level position with quick advancement opportunities. As Data Analyst you will focus on data and corpus labeling, as well as other data-related tasks critical to supporting our large language models (LLMs) and cybersecurity initiatives. This role is crucial in enhancing our products capabilities by ensuring the accuracy and quality of the data used to train models and detect threats, thereby supporting the overall mission of the Generative AI Research Center.
CrowdStrike is a cybersecurity company, but we do not require candidates for this role to have prior security industry experience. We will mentor and train in security topics as needed. We do expect a strong interest in CrowdStrike's mission and a willingness to engage with the needs of our product teams and customers.

If you are a hands-on engineer who loves technical challenges and wants to operate at scale, apply & let's talk!

Interviewing process: online and onsite where applicable

What You'll Do:

• Label and annotate cybersecurity-related datasets to prepare them for analysis and machine learning tasks.

• Ensure labeling accuracy and consistency across different datasets, including threat intelligence data, incident reports, network logs, etc.

• Gather data from various cybersecurity sources, including threat intelligence feeds, logs, and internal reports.

• Clean and preprocess data to make it suitable for analysis and modeling

• Perform exploratory data analysis to uncover patterns, trends, and insights related to cybersecurity threats and vulnerabilities.

• Utilize statistical methods and tools to interpret data and identify potential security issues.

• Create and maintain dashboards and reports to communicate findings to cybersecurity stakeholders.

• Develop visualizations to present data in a clear and concise manner, highlighting key security metrics and trends.

• Work closely with analysts, data scientists, engineers, and other team members to support their data needs.

• Support the implementation and optimization of MLOps pipelines, leveraging data insights to deploy, monitor and scale machine learning models for different solutions.

• Participate in team meetings and contribute to project planning and discussions, providing data-driven insights.

• Document processes, methodologies, and insights gained from data analysis and labeling activities.

• Maintain clear records of data sources, cleaning steps, and labeling criteria to ensure reproducibility and auditability.

What You'll Need:

• Bachelor's degree in Computer Science or related STEM field.

• Proficiency in data manipulation and analysis tools (e.g., Python, SQL).

• Familiarity with relevant libraries and frameworks (e.g., TensorFlow, PyTorch).

• Experience with data labeling and annotation tools.

• Strong analytical and problem-solving skills, with an understanding of cybersecurity concepts.

• Excellent communication and collaboration abilities.

• Attention to detail and a commitment to data accuracy.

Tech Stack (not mandatory to know everything; a robust learning capacity is essential):

• Python

• SQL

• Data Labeling and Annotation Tools like Labelbox, Prodigy, etc.

• Data Analysis and Visualization like Pandas, NumPy, Matplotlib, Seaborn, etc.

• Docker

• Kubernetes

• AWS

• Kafka

• GIT

Bonus Points:

• Existing exposure to Go, AWS, Cassandra, Kafka, Elasticsearch.

• Experience with Language Models, Data Science, Data Engineering.

• Experience with data labeling and annotation tools, particularly in a cybersecurity context.

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Benefits of Working at CrowdStrike:

• Remote-first culture

• Market leader in compensation and equity awards with option to participate in ESPP in eligible countries

• Competitive vacation and flexible working arrangements

• Physical and mental wellness programs 

• Paid parental leave, including adoption 

• A variety of professional development and mentorship opportunities

• Access to CrowdStrike University, LinkedIn Learning and Jhanna

• Offices with stocked kitchens when you need to fuel innovation and collaboration

• Birthday time-off in your local country

• Work with people who are passionate in our mission and Great Place to Work certified across the globe