Antifraud Analyst-Risk & Security

Daraz; Karachi Division; On-site; PKR 60,000 - 90,000; Full time

Job summary

Daraz is seeking an Antifraud Analyst to support detection, investigation, and resolution of fraud across Pakistan, Bangladesh, Sri Lanka, and Nepal. You will combine hands-on casework with data analytics and end-to-end project ownership.

Responsibilities include investigating cases of incentive abuse, account security, seller and buyer risk, and cross-functional collaboration with Strategy, Product, Tech, and Operations to test rules and roll out new controls. English communication is essential.

Qualifications

• Bachelor's degree in Computer Science, Statistics, Business, Finance or a related quantitative field.
• 2–3 years of experience in analytics, fraud operations, or risk management within e-commerce or digital services.
• Proficiency in SQL for data extraction, manipulation, and analysis across large datasets.
• Hands-on experience building dashboards or reports using Tableau, Power BI, Metabase, or equivalent.
• Strong attention to detail and ability to manage multiple cases and workstreams under SLA pressure.
• Clear written and verbal communication skills in English.

Responsibilities

• Investigate and resolve fraud cases across domains including incentive abuse, account security, seller risk, and buyer protection; document findings accurately and close cases within SLA.
• Analyze case-level data using SQL to surface emerging fraud trends and feed insights into detection strategy.
• Build and maintain dashboards and reports tracking fraud metrics across regions for leadership.

Skills

English proficiency

Analytical thinking

Attention to detail

Education

Bachelor's degree in Computer Science, Statistics, Business, Finance or related quantitative field

Tools

SQL

Tableau

Power BI

Metabase

Python

Job description

As an Antifraud Analyst within the Risk & Security team, you will support the detection, investigation, and resolution of fraud across our regional markets covering Pakistan, Bangladesh, Sri Lanka, and Nepal, combining hands‑on casework with data analytics and end‑to‑end project ownership.

• Case Investigation & Resolution: Investigate and resolve fraud cases across domains including incentive abuse, account security, seller risk, and buyer protection; document findings accurately, expedite where required, and close cases within SLA.


• Fraud Pattern Analysis: Analyze case-level data using SQL to surface emerging fraud trends, identify risk signals across markets, and feed insights back into detection and strategy discussions.


• Analytics & Dashboard Development: Build and maintain dashboards and reports that track key fraud metrics across the team's operational domains; translate data into clear narratives for team leads and stakeholders.


• Project Management: Own antifraud initiatives end to end; from problem definition and scoping through to execution, monitoring, and post-implementation review; maintain documentation and surface blockers proactively.


• Cross-functional Coordination: Work closely with internal teams across Strategy, Product, Tech, and Operations to support rule testing, process improvements, and the rollout of new controls.

Job Requirements

• Bachelor's degree in Computer Science, Statistics, Business, Finance or a related quantitative field.


• 2–3 years of experience in analytics, fraud operations, or risk management within e-commerce or digital services.


• Proficiency in SQL for data extraction, manipulation, and analysis across large datasets is a must.


• Hands‑on experience building dashboards or reports using tools such as Tableau, Power BI, Metabase, or equivalent.


• Strong attention to detail and ability to manage multiple cases and workstreams under SLA pressure.


• Clear written and verbal communication skills in English.

Preferred

• Familiarity with e‑commerce fraud typologies such as incentive abuse, account takeover, seller fraud, and buyer protection cases.


• Experience working across multiple markets or in a regional operations capacity.


• Basic proficiency in Python for data analysis or automation.