Security Operations Engineering - Fraud & Abuse at Microsoft

, , United States -

Full Time

Start Date

Immediate

Expiry Date

20 Feb, 26

Salary

0.0

Posted On

22 Nov, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Fraud Detection, Cyber Security, Anomaly Detection, Threat Modeling, Incident Response, Data Analytics, Technical Documentation, Process Automation, Python, PowerShell, SIEM, SQL, Machine Learning, Digital Forensics, Penetration Testing, Malware Analysis

Industry

Software Development

Description

Working as a part of the Centralized Fraud Abuse Risk team (CFAR), you will work to solve issues related to the latest fraud and abuse trends and early warning indicators, as well as help design solutions for emerging threats. Prioritize alerts and issues and perform triage to confirm security incidents Performing analysis on true positive alerts to determine root cause and impact. Collaborate with teams to create and potentially execute incident mitigation and remediation plans. Create technical documentation for other analysts and other teams to follow. Support cross company incidents and crisis. Doctorate in Statistics, Mathematics, Computer Science, or related field OR Master's Degree in Statistics, Mathematics, Computer Science, or related field AND 3+ years experience in software development lifecycle, large-scale computing, threat modeling, cyber security, anomaly detection, Security Operations Center (SOC) detection, threat analytics, security incident and event management (SIEM), information technology (IT), or operations incident response OR Bachelor's Degree in Statistics, Mathematics, Computer Science, or related field AND 4+ years experience in software development lifecycle, large-scale computing, threat modeling, cyber security, anomaly detection, Security Operations Center (SOC) detection, threat analytics, security incident and event management (SIEM), information technology (IT), or operations incident response These requirements include, but are not limited to the following specialized security screenings: Doctorate in Statistics, Mathematics, Computer Science, or related field AND 3+ years experience in software development lifecycle, large scale computing, threat modeling, cyber security, or anomaly detection OR Master's Degree in Statistics, Mathematics, Computer Science, or related field AND 6+ years experience in software development lifecycle, large scale computing, threat modeling, cyber security, or anomaly detection OR Bachelor's Degree in Statistics, Mathematics, Computer Science, or related field AND 8+ years experience in software development lifecycle, large scale computing, threat modeling, cyber security, or anomaly detection OR equivalent experience. CISSP CISA CISM SANS OSCP Security+ 5+ years of experience in anti-abuse/anti-fraud/anti-cybercrime space OR in a field that has transferrable hands-on technical skills such as: cyber security threat intelligence, security research, etc. 7+ years of experience in software development lifecycle, large-scale computing, modeling, cyber security, anomaly detection, Security Operations Center (SOC) detection, threat analytics, security incident and event management (SIEM), information technology (IT), and operations incident response 3+ years of experience in applying big data analytics techniques to solve security problems. CISSP, CISA, CISM, SANS, GCIA, GCIH, OSCP, and/or Security+ certification. Exposure to security-related subjects and trends such as digital forensics, reverse engineering, penetration testing, and malware analysis. Prior experience working with large data sets analytics to answer complex and ambiguous questions using tools and languages like: SQL, KQL/Azure Data Explorer, Jupyter Notebook, Spark, R, U-SQL, Azure Synapse, Azure Machine Learning, Azure Data Lake, Python, or PowerBI. Experience in creating and improving process automation and tools/systems/API integration using Python or PowerShell.

Responsibilities

You will work to solve issues related to the latest fraud and abuse trends and early warning indicators, as well as help design solutions for emerging threats. Collaborate with teams to create and potentially execute incident mitigation and remediation plans.