Security/fraud analyst

Responsibilities and Outcomes
 

Forensic Investigations & Detection

•  Acts as front-line security gatekeeper for Microsoft's online advertising marketplace; perform forensics on the platform to identify and fight fraud, malware and other unsafe advertising practices.
• Identifies concerning or anomalous trends and patterns posing ad quality risks and violations.
• Seeks to mitigate ad traffic and quality risks or other out of compliance activity on the network through existing detection mechanisms as well as helping device new ones.
• Acts to prevent user, partner and customer quality risk issues through industry awareness, new feature risk analysis, progressive policy influence, pre-launch partner quality reviews, fraud/DSAT trend identification, platform feature recommendations and business quality advocacy.
• Works to progressively evolve detection and investigation methodologies by working closely with FTEs and engineering stakeholders.
• Captures, records, and analyzes events to discover the source of security and user/advertiser safety attacks or other problem incidents using standard and custom forensic systems.
•  Perform threat hunting as a part of core responsibility, during instances of phishing/malware, performs activities but not limited to finding all similar domains and add blocks and protection.
• Fraud Hunt: Work in tangent with the Microsoft team, implement and run proactive sweeps based on various threats, perform new targeted net sweeps, ensure more accurate sweep detections with less account disruption, and conduct targeted sweeps based on email domains, advertiser names, payment methods, country, Trinity links, etc.
• Support Customer FTEs on escalations/patterns: Investigate large fraud/user safety cases by sending all relevant information in a way that best achieves desired results.
•  Escalation Help: Assist with different escalation types like takedowns, phishing, malware, other high urgency escalations requiring immediate actions.
• Should be capable of documenting existing processes and training new vendors in process and policy.
• Be able to demonstrate a deep understanding of the changing fraud landscape as well as adapt to new techniques and processes.
• Analyzes extraordinarily large volumes of data, interprets traffic patterns, identifies risks, documents conclusions, and recommends systems and process solutions to mitigate issues.
• Influences engineering platform improvements by identifying root cause trends for False Positives/False Negatives and submitting user cases documenting platform gaps.
• Drives customer-centric enforcement of security policies through fraud and quality investigations and root cause mitigation at scale.
• Enforces marketplace and user security by recognizing and adapting to industry shifts, evolving client needs/risks and emerging technological conditions.
•  Continuously deploys creative, scalable solutions to supplement existing engineering platform risk detections to limit risk and exposure until new platform features are deployed.
•  Ensures policy interpretation and enforcement are enabled at scale.
  • Takes enforcement actions against fraud through escalation/alert responses and account closures.
  •  Influences strategic Policy Compliance business decisions by documenting risks identified through investigations, quality reviews, and post-onboarding compliance checks.
  • Leverages and improves operational tools or methods, and makes algo-platform recommendations, to proactively identify fraud/DSAT.
  •  Uses repeatable processes and automations to improve consistency, efficiency, and safety.
  •  Fosters Service Level Agreement (SLA) achievement by surfacing risks, issues, trends, and performing quality reviews through workflow monitoring, auditing, and timely issue mitigation.
     

5+ years relevant technical experience.
• 3+ years working in security and/or online forensics.
• 3+ years working with Data and Trend Analysis, data visualization skills and ability to represent extremely large data sets.
• Experience with Excel, PowerBI and Microsoft suite of standard applications.
• Strong documentation skills to be utilized for case management, knowledge capture, bug management and training
• Work well independently, ability to manage one's time, as well as strong cross and group collaboration and interpersonal skills
• English language skills including strong verbal and written communication skills required for all levels of stakeholders. Strong understanding of the North American and European cultures, slang, brands, and current events.
• Must be well-organized with strong attention to detail & commitment to Quality
• Adherence to quality, accuracy and stated policy standards.
• Self-Motivated to identify, solve, and drive for results.
• Collaborative and positive team member.
• Experience working with Global Teams.
• Occasional night and weekend on-call work.
 

Preferred Experiences, and Skills

• Experience in organic and paid search.
•  Experience in any of the following areas: data science, data mining, web mining, machine learning, statistics, business intelligence/customer intelligence, user modeling, information retrieval, databases, data warehousing, data processing (ETL), e-metrics/measurement.
•  Experience in Machine Learning and Data Science.
•  Experience in fraud, risk mitigation, cyber security or similar lines of business.
  Other Requirements
•  Working hours must be primarily during US Pacific time zone Monday through Friday to work with US based team.
•  Resource to align to US holidays/working days
•  Strong written language capability in western English
• Microsoft suite of products on the employer provided computer: Teams, PowerPoint, Outlook, Excel, Word, Power BI etc.

Must have technic skills: Core Technical Skills

•  SQL (Must-have)
  • Ability to write complex queries
  • Joins, CTEs, window functions
  • Data extraction for investigation & audit
  • Example use: Pulling case history, entity-level transactions, linking accounts
• Excel / Advanced Data Analysis
  • Pivot tables, VLOOKUP/XLOOKUP, Power Query
  • Building dashboards
  • Trend, variance, and anomaly analysis
•  Data Visualization Tools
  • Power BI / Tableau
  • Creating fraud trend dashboards
  • Building models to show patterns (clusters, spikes)