Data Analyst - Compliance Analytics

TerraPay

2 - 6 years

7 - 11 Lacs

bengaluru

Posted:-1 days ago| Platform:

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Skills Required

computer science data analysis automation analytical data mining microsoft analytics monitoring sql python

Work Mode

Work from Office

Job Type

Full Time

Job Description

As a Data Analyst in the Compliance Analytics team, you will play a key role in safeguarding financial integrity by leveraging data to detect and prevent financial crimes. Your responsibilities include:

Analyzing transaction data to uncover patterns of money laundering and fraud.
Supporting sanctions screening with advanced data insights.
Developing and maintaining SQL and Python scripts for data operations.
Creating interactive dashboards and reports using BI tools like Power BI or Tableau.
Implementing basic predictive models for fraud scoring and anomaly detection.
Handling BAU data requests and generating QA samples for monitoring and screening.
Contributing to AI-driven initiatives within the compliance function.

How will you create an impact

Key Responsibilities

Transaction Monitoring
: Develop rules and statistical algorithms to flag suspicious transactions in real time.
Sanctions Screening
: Perform data preparation for customer and transaction screening against global and regional sanctions lists (e.g., OFAC, UN, EU) as and when required, investigate and prepare analytical insights as per the requirement of the team, and collaborate with team members to tune screening rules and reduce false positives.
Pattern Analysis
: Identify money laundering typologies (e.g., structuring, layering) through data mining and clustering techniques.
Predictive Analytics
: Prototype and validate models for fraud detection, monitor model performance, and refine thresholds.
Dashboarding & Reporting
: Design and maintain dashboards for compliance metrics, KPI tracking, and regulatory reporting.

Stakeholder Collaboration:
Work with Compliance Operations, Risk, and IT teams to translate business requirements into analytical solutions

Essential qualifications:

Education: Bachelor s or Master s degree in Statistics, Mathematics, Computer Science, or related field.
Python: Proficient in pandas, NumPy, and SciPy for data analysis.

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