We are seeking a highly skilled and motivated Cyber Data Analyst to join our dynamic team.
The ideal candidate will be proficient in working with both structured and unstructured data, utilizing a variety of databases including GraphDB, VectorDB, ColumnDB, Elasticsearch, and other NoSQL databases.
This role involves leveraging Python to explore data, extract insights, present trends, and make predictions.
Responsibilities:
Advanced Data Exploration: Apply Python and statistical tools to deeply explore structured and unstructured data across various database technologies (GraphDB, VectorDB, ColumnDB, Elasticsearch, and NoSQL).
Insight and Trend Analysis: Extract meaningful insights from complex data sets to identify trends, patterns, and anomalies.
In-depth Research: Research up-to-date threat-intelligence repositories and automate data enrichments into the platform.
Data-Driven Cybersecurity Analysis: Utilize advanced statistical methods and mathematical modeling to analyze data for potential threats and vulnerabilities, focusing on patterns and anomalies that could indicate security incidents.
Collaborative Insight Sharing: Work alongside cross-functional teams to communicate complex data findings. Prepare and present reports that translate intricate data insights into actionable intelligence for both technical and non-technical stakeholders.
Continuous Skill Enhancement: Stay updated with the latest statistical methods, data analysis techniques, and advancements in AI, including machine learning and deep learning, to continually improve cybersecurity data analysis practices.
The ideal candidate will be proficient in working with both structured and unstructured data, utilizing a variety of databases including GraphDB, VectorDB, ColumnDB, Elasticsearch, and other NoSQL databases.
This role involves leveraging Python to explore data, extract insights, present trends, and make predictions.
Responsibilities:
Advanced Data Exploration: Apply Python and statistical tools to deeply explore structured and unstructured data across various database technologies (GraphDB, VectorDB, ColumnDB, Elasticsearch, and NoSQL).
Insight and Trend Analysis: Extract meaningful insights from complex data sets to identify trends, patterns, and anomalies.
In-depth Research: Research up-to-date threat-intelligence repositories and automate data enrichments into the platform.
Data-Driven Cybersecurity Analysis: Utilize advanced statistical methods and mathematical modeling to analyze data for potential threats and vulnerabilities, focusing on patterns and anomalies that could indicate security incidents.
Collaborative Insight Sharing: Work alongside cross-functional teams to communicate complex data findings. Prepare and present reports that translate intricate data insights into actionable intelligence for both technical and non-technical stakeholders.
Continuous Skill Enhancement: Stay updated with the latest statistical methods, data analysis techniques, and advancements in AI, including machine learning and deep learning, to continually improve cybersecurity data analysis practices.
Requirements:
Proven experience working with structured and unstructured data, and familiarity with databases such as GraphDB, VectorDB, ColumnDB, Elasticsearch, and other NoSQL databases.
Expertise in Python for data exploration, analysis, and visualization.
Solid understanding of cybersecurity principles and experience in applying them to data analysis.
Experience in machine learning, deep learning, and large language models is highly desirable.
Strong analytical and problem-solving skills, with the ability to communicate complex data insights clearly and effectively.
Excellent collaboration and communication skills, with a proven track record of working effectively in team environments.
Bachelors degree in Computer Science, Cybersecurity, or a related field is a plus.
Cybersecurity threat intelligence background and proficiency in webint is a plus.
Proven experience working with structured and unstructured data, and familiarity with databases such as GraphDB, VectorDB, ColumnDB, Elasticsearch, and other NoSQL databases.
Expertise in Python for data exploration, analysis, and visualization.
Solid understanding of cybersecurity principles and experience in applying them to data analysis.
Experience in machine learning, deep learning, and large language models is highly desirable.
Strong analytical and problem-solving skills, with the ability to communicate complex data insights clearly and effectively.
Excellent collaboration and communication skills, with a proven track record of working effectively in team environments.
Bachelors degree in Computer Science, Cybersecurity, or a related field is a plus.
Cybersecurity threat intelligence background and proficiency in webint is a plus.
This position is open to all candidates.
