Information Technology
Full-Time
Xpetize
Overview
Job Title : Fraud Data Scientist
Location : Bangalore
Experience : 3+ years
Employment Type : Full-time
Industry : Finance, FinTech, E-commerce, Banking, etc.
About The Role
We are seeking a highly analytical and detail-oriented Fraud Data Scientist with 3+ years of experience to join our Risk & Fraud Analytics team. In this role, you will leverage data science, machine learning, and domain expertise to detect, investigate, and prevent fraudulent activities across our platforms. You will play a critical role in safeguarding customer trust and minimizing financial losses.
Key Responsibilities
Required Qualifications
(ref:hirist.tech)
Location : Bangalore
Experience : 3+ years
Employment Type : Full-time
Industry : Finance, FinTech, E-commerce, Banking, etc.
About The Role
We are seeking a highly analytical and detail-oriented Fraud Data Scientist with 3+ years of experience to join our Risk & Fraud Analytics team. In this role, you will leverage data science, machine learning, and domain expertise to detect, investigate, and prevent fraudulent activities across our platforms. You will play a critical role in safeguarding customer trust and minimizing financial losses.
Key Responsibilities
- Develop, implement, and maintain machine learning models for fraud detection and prevention.
- Analyze transactional, behavioral, and external data to identify fraud patterns and risk indicators.
- Partner with engineering and product teams to deploy models into production and monitor performance.
- Conduct root-cause analysis of fraud cases and propose scalable solutions to prevent
- Create dashboards, reports, and alerts to monitor key fraud KPIs and emerging threats.
- Work with stakeholders across risk, compliance, legal, and customer service to define fraud strategies.
- Continuously improve model accuracy, reduce false positives, and adapt to evolving fraud
Required Qualifications
- 3+ years of experience in data science, analytics, or a similar role focused on fraud, risk, or trust & safety.
- Strong proficiency in Python, SQL, and machine learning libraries (e.g., scikit-learn, XGBoost, LightGBM).
- Experience with data visualization tools such as Tableau, Power BI, or Looker.
- Solid understanding of fraud typologies (identity theft, synthetic fraud, transaction fraud, etc.).
- Familiarity with real-time data pipelines and production model deployment (preferred: Spark,
- Strong problem-solving skills and the ability to work independently in a fast-paced
- Excellent communication skills with the ability to explain complex models to non-technical
(ref:hirist.tech)
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