The Cyber Fusion Center protects the business by combining threat intelligence, monitoring, detection engineering, incident response, and security automation into one proactive, intelligence-led defense capability.
Responsibilities and Impact
Design, develop, test, and maintain high-quality detections for various threats
Develop detection logic across multiple security platforms using tools like Splunk SPL, Microsoft Sentinel KQL, and Elastic Query DSL
Apply artificial intelligence, machine learning, and data science techniques to identify anomalous behavior and emerging threats
Build and maintain security analytics and data pipelines using Python, SQL, and other tools
Perform feature engineering, statistical analysis, and model development for security use cases
Conduct threat hunting and hypothesis-driven investigations to identify gaps in existing detection coverage
Collaborate with various teams to develop effective detection capabilities
Implement detection-as-code practices and support purple-team exercises
Explore the use of Generative AI, Large Language Models, and Agentic AI to improve threat research and detection development
Develop Power BI dashboards and reports to communicate detection coverage and alert trends
Document detection logic, data sources, and analytical methods
What We're Looking For
Five or more years of experience in cybersecurity, threat detection, or a related field
Strong knowledge of security operations, incident response, and threat intelligence
Hands-on experience developing detections for security platforms
Strong Python and SQL skills, including experience processing large security datasets
Practical experience with data science and machine learning methods
Experience with Python libraries like Pandas, NumPy, and scikit-learn
Experience using Databricks, data lakes, and large-scale data processing platforms
Understanding of MITRE ATT&CK and the detection engineering lifecycle
Strong analytical, problem-solving, documentation, and communication skills
What's In It For You?
Health & Wellness: health care coverage designed for the mind and body
Flexible Downtime: generous time off to keep you energized
Continuous Learning: access to resources to grow your career and learn new skills
Invest in Your Future: competitive pay, retirement planning, and financial wellness programs
Family Friendly Perks: benefits for your partners and family members
This page helps Indian job seekers prepare for Python interviews for backend, data engineering and data analyst roles, whether you are a fresher facing your first technical round or an experienced developer aiming for a senior position. It has 60 questions in three levels, easy, medium and hard, each with a concise sample answer and, where it helps, runnable Python 3.12 code. Topics include data structures, OOP, generators, decorators, the GIL and concurrency, type hints, testing and performance. Answer each question aloud in your own words first, then compare with the sample answer and run the code to check your understanding.
Questions you may be asked
What is the difference between mutable and immutable types in Python?
What is the difference between a list and a tuple?
