Job Description – Assistant Manager Fraud Analytics
Purpose of the Role
To leverage advanced data analytics, statistical techniques, and machine learning approaches to extract actionable insights from business data. The role focuses on identifying fraud patterns, improving risk controls, enhancing operational efficiency, and supporting data-driven decision-making.
Key Responsibilities
- Identify, collect, and extract data from multiple internal and external sources.
- Perform data cleaning, data wrangling, and transformation activities to ensure data accuracy and usability.
- Develop and maintain efficient data pipelines for automated data processing and analytics.
- Design and apply statistical and machine learning models to identify patterns, trends, and relationships within data.
- Build predictive models to detect potential fraud risks, forecast outcomes, and support business decisions.
- Analyze fraud trends, investigate data issues, and provide actionable insights.
- Perform data quality checks, lineage analysis, and identify authoritative data sources.
- Collaborate with business stakeholders to identify opportunities where analytics can create value.
- Prepare analytical reports and communicate findings to stakeholders.
- Support risk management initiatives by strengthening controls and improving fraud detection processes.
Required Skills & Experience
- Strong expertise in SQL, SAS, Data Analytics, and Reporting.
- Experience in fraud analytics, risk analytics, transaction monitoring, or banking analytics.
- Strong analytical and problem-solving skills with the ability to interpret complex datasets.
- Experience in statistical analysis and predictive modelling.
- Knowledge of machine learning techniques and data science methodologies.
- Understanding of data pipelines, ETL processes, and automated data processing.
- Ability to investigate and resolve data quality, control, and reporting issues.
- Strong communication skills with the ability to present insights and collaborate with stakeholders.
Candidate Profile
- Experience working with large datasets in a banking, financial services, fintech, or risk analytics environment.
- Ability to make data-driven decisions and manage analytical projects independently.
- Strong attention to detail with a focus on risk mitigation and process improvement.
Work Schedule
Shift: 11:00 AM – 8:00 PM
Work Model: 2 days Work From Office + 3 days Work From Home
