Experienced Remote Data Analyst – Cybersecurity Data Analysis and Machine Learning Support Specialist
Introduction to CrowdStrike and Our Mission
CrowdStrike is a global leader in cybersecurity, dedicated to protecting our customers from the most sophisticated cyberattacks. Our market-leading cloud-native platform has revolutionized the industry, and we're committed to continuing innovation and excellence. We're passionate about stopping breaches and making the digital world a safer place. As a remote-first company, we offer a unique and flexible work environment that allows our team members to thrive and grow professionally while maintaining a healthy work-life balance.
About the Role: Data Analyst in Our Generative AI Research Center
We're seeking a highly motivated and detail-oriented Data Analyst to join our growing Generative AI Research Center. This is an exceptional opportunity for a junior or entry-level professional to launch their career in a dynamic and rapidly evolving field. As a Data Analyst, you will play a critical role in supporting our large language models (LLMs) and cybersecurity initiatives by ensuring the accuracy and quality of the data used to train models and detect threats. Your work will be instrumental in enhancing our products' capabilities and contributing to the overall mission of the Generative AI Research Center.
Key Responsibilities:
- Label and annotate cybersecurity-related datasets to prepare them for analysis and machine learning tasks, ensuring accuracy and consistency across different datasets.
- Gather data from various cybersecurity sources, including threat intelligence feeds, logs, and internal reports, and clean and preprocess the 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, utilizing statistical methods and tools to interpret data and identify potential security issues.
- Create and maintain dashboards and reports to communicate findings to cybersecurity stakeholders, developing visualizations to present data in a clear and concise manner and highlighting key security metrics and trends.
- Collaborate closely with analysts, data scientists, engineers, and other team members to support their data needs, participating in team meetings and contributing to project planning and discussions with data-driven insights.
- Support the implementation and optimization of MLOps pipelines, leveraging data insights to deploy, monitor, and scale machine learning models for different solutions, and document processes, methodologies, and insights gained from data analysis and labeling activities.
Essential Qualifications:
- Bachelor's degree in Computer Science or a related STEM field, with a strong foundation in data analysis, machine learning, and programming.
- Proficiency in data manipulation and analysis tools, such as Python, SQL, and relevant libraries and frameworks like TensorFlow and PyTorch.
- Experience with data labeling and annotation tools, and strong analytical and problem-solving skills, with an understanding of cybersecurity concepts.
- Excellent communication and collaboration abilities, with attention to detail and a commitment to data accuracy.
Preferred Qualifications:
- Existing exposure to Go, AWS, Cassandra, Kafka, Elasticsearch, and experience with Language Models, Data Science, and Data Engineering.
- Familiarity with data labeling and annotation tools, particularly in a cybersecurity context, and experience working with large datasets and machine learning models.
- A robust learning capacity, with a willingness to learn and adapt to new technologies and tools, and a strong interest in CrowdStrike's mission and a willingness to engage with the needs of our product teams and customers.
Skills and Competencies:
To succeed in this role, you will need to possess a unique combination of technical, business, and interpersonal skills, including:
- Strong technical skills, with proficiency in programming languages like Python, and experience with data analysis and machine learning tools and technologies.
- Excellent analytical and problem-solving skills, with the ability to collect, analyze, and interpret large datasets, and identify trends and patterns.
- Effective communication and collaboration skills, with the ability to work closely with cross-functional teams, including analysts, data scientists, engineers, and other stakeholders.
- A strong understanding of cybersecurity concepts and principles, with the ability to apply this knowledge to real-world problems and scenarios.
- A commitment to data accuracy and quality, with attention to detail and a focus on delivering high-quality results.