Data Science and Cybersecurity: A match made in cyberheaven
As we enter the age of AI, the classical picture of what constitutes a cyber threat has changed. Modern threats are fast, hyper adaptable, and intelligent. Cybercriminals are infiltrating both public and private life at a rate we’ve never seen before. From banks and grocery stores to major commercial ports and/or naval vessels, cybercriminals have used the evolving technological landscape to their advantage. To stay ahead of the curve, cybersecurity firms must go on the offensive by employing data analysts and scientists who can turn vast amounts of raw information into actionable intelligence. Two of the fastest growing sectors in tech have started to merge and cybersecurity firms need to catch up. Let’s take a look at some of the reasons why.
Cybersecurity and data science are two of the fastest growing fields in the U.S. The need for trained professionals who can analyze massive datasets and help a firm shift from reactive to proactive is becoming a necessity. Cybersecurity firms will often use data scientists to analyze information and look for patterns or anomalies that can help to create a proactive response to future threats. This is crucial for companies today. The stakes of a cybercrime have never been higher and the cost per breach is rising, regardless of what industry you work for. Data scientists can use predictive data models and machine learning to identify key behaviors and trends in order to stop a future attack.
What are we looking for?
The modern data scientists looking for a career in cybersecurity must have a certain set of skills. Some of the skills and requirements we’re looking for include:
TS/SCI w/FS Polygraph clearance.
Al/ML experience to impact and assess large datasets. This includes data modeling, computational mathematics, qualitative and quantitative techniques, data visualizations and Al/ML model development and deployment.
Advanced statistical and predictive modeling.
Large-scale data processing {e.g., Spark, cloud data platforms).
Python and SQL proficiency.
Data visualization using Tableau, Power Bl, or Python libraries. Automated analytics workflow development.
Ability to translate complex data into strategic insights.
Check out our current openings, or send your resume to recruiter Jeff Morris at recruiting@warcollar.com.
