Cybersecurity Data Engineer (Hybrid)

Key Skills

Apache Hadoop, Cybersecurity, Data Analytics, Data Mining, Data science techniques, Data Visualization, Effective communication skills, Java Programming, Machine learning techniques, PowerBI, Presentation skills, Python Programming, PyTorch, R Programming, Scikit-learn, Spark Core, Statistics, Tableau, TensorFlow

Job Description

Work Flexibility: Hybrid

Who we Want:

• Dedicated achievers. People who thrive in a fast-paced environment and will stop at nothing to ensure a project is complete and meets regulations and expectations.
• Analytical problem solvers. People who go beyond just fixing to identify root causes, evaluate optimal solutions, and recommend comprehensive upgrades to prevent future issues.
• Goal-oriented: Keeping the customer and requirements squarely in focus, people who deliver safe and robust solutions. 
• Detail-oriented process improvers. Critical thinkers who naturally see opportunities to develop and optimize work processes – finding ways to simplify, standardize and automate.

Job description

We are seeking a highly skilled and motivated Cyber Security Data Scientist to join our team. As a Cyber Security Data Scientist, you will play a critical role in ensuring the security of our organization's digital assets and infrastructure. You will apply advanced data analytics and machine learning techniques to analyze and detect potential cyber threats, identify vulnerabilities, and develop proactive security measures. Your expertise will help shape our cyber security strategy and drive data-driven decision-making processes.

What you will do:

• Develop and implement data analysis models and algorithms to detect, analyze, and predict cyber security threats and vulnerabilities.
• Design and develop machine learning models to identify patterns and anomalies in large-scale data sets related to cyber security.
• Collaborate with cross-functional teams, including security analysts, engineers, and data scientists, to identify data requirements and define metrics for evaluating security risks.
• Analyze and interpret complex data sets from various sources, such as network logs, security incident reports, and threat intelligence feeds.
• Conduct research and stay updated on the latest cyber security threats, attack vectors, and defense mechanisms.
• Develop and maintain statistical models and algorithms for anomaly detection, intrusion detection, and fraud detection.
• Collaborate with the software development team to integrate data science solutions into security systems and tools.
• Provide insights and recommendations to improve security posture and response capabilities based on data analysis findings.
• Develop and deliver reports, presentations, and visualizations to communicate key findings and recommendations to stakeholders and senior management.
• Participate in incident response activities, including forensic analysis, threat hunting, and incident investigations.

• Evaluate and test new security technologies and tools to enhance the organization's cyber security capabilities.
• Stay abreast of emerging trends and advancements in cyber security, data science, and machine learning.

What you need:

• Bachelor's degree in Computer Science, Data Science, Cyber Security, or a related field. A Master's or Ph.D. degree is preferred.
• Minimum 4 years relevant experience is required.
• Proven experience working as a Data Scientist, preferably in the field of cyber security.
• Strong understanding of cyber security principles, attack vectors, and defense mechanisms.
• Proficiency in data analytics, statistical analysis, and machine learning techniques.
• Experience with programming languages such as Python, R, or Java, and data science libraries (e.g., TensorFlow, PyTorch, scikit-learn).
• Familiarity with big data technologies and frameworks (e.g., Hadoop, Spark) and distributed computing concepts.
• Knowledge of data visualization tools (e.g., Tableau, Power BI) to present complex data in a clear and concise manner.
• Solid understanding of network protocols, log analysis, and data mining techniques.
• Strong problem-solving skills and the ability to work independently as well as collaboratively in a team environment.
• Excellent communication skills with the ability to translate technical findings into actionable recommendations for non-technical stakeholders.
• Industry certifications such as Certified Information Systems Security Professional (CISSP), Certified Ethical Hacker (CEH), or Certified Data Scientist (CDS) are a plus.
• Strong ethics and a commitment to maintaining confidentiality and integrity in handling sensitive data.

Other requirements:

• Strong collaboration and influencing skills are required. The successful candidate must have the ability to persuade and build consensus cross-functionally as an evangelist in a team-oriented fashion. The candidate must be able to inspire and motivate the organization as the transformation activities continue across IT and within the business. 
• Excellent communication skills. Communication across the enterprise will be important as this leader will often be tasked with leading cross-functional teams as he/she executes these large-scale programs and projects. The successful candidate must effectively communicate cross-functionally and at a variety of levels within the organization. 
• Organization & Strategic Agility. The successful candidate must have a high degree of situational awareness and ability to navigate complex issues and channels to successfully deliver solutions in partnership with business and IT leadership teams.
• High Energy & Stamina. Proven capabilities in persevering through cultural and political hurdles with balanced optimism to drive and deliver on managed service strategies / objectives.
• Process, Cost & Metrics Champion. Process and continuous improvement zealot with strong analytical skills in identifying and building new opportunities and offerings. Must be able to consistently drive outcomes through influence and measurement rather than