Fraud Modeling Analyst
Bengaluru, KA, IN
- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
Full-time — employment source
## Time Type: Full time \------------------------------------------------------
Employment type in the employer’s listing: FULL_TIME
From the employer’s posting
What you’ll work on
Full postingPartner closely with Strategy partners and Model Risk Management validators across the model lifecycle including validation, ongoing performance evaluation, and annual reviews.
From the employer’s posting
Responsibilities: Partner closely with Strategy partners and Model Risk Management validators across the model lifecycle including validation, ongoing performance evaluation, and annual reviews. * Responsible for model development, validation and testing of fraud detection models, including statistical analysis, data validation and model performance evaluation. * Conduct rigorous validation assessment for fraud model validation; develop and implement validation methodologies to assess model accuracy, robustness, and effectiveness. * Ensure compliance with regulatory requirements and industry best practices in fraud detection and model validation. * Incumbents work with large and complex data sets (both internal and external data) to evaluate, recommend, and support the implementation of business strategies. * Identifies and compiles data sets using a variety of tools (e.g. Hive, SQL) to help predict, improve, and measure the success of key business to business outcomes * Responsible for documenting data requirements, data collection / processing / cleaning, and exploratory data analysis, which may include utilizing statistical models / algorithms and data visualization technique. * Appropriately assess risk when business decisions are made, demonstrating particular consideration for the firm's reputation and safeguarding Citigroup, its clients and assets, by driving compliance with applicable laws, rules and regulations, adhering to Policy, applying sound ethical judgment regarding personal behavior, conduct and business practices, and escalating, managing and reporting control issues with transparency.
What you’ll bring
All qualificationsCore experience
- Familiarity with data extraction tools like Hive will be an advantage.
Qualification wording
* 3+ years of hands-on analytical experience * 2+ years’ experience in statistical analysis with working knowledge of at least one of the following statistical software packages: Python (Must), Hive, Spark, SAS * Strong quantitative, analytical, and problem-solving skills; knowledge of probability theory, statistics, mathematical finance, econometrics, numerical methods * Strong understanding of statistical concepts and modelling techniques including traditional and advanced ML algorithms * Strong proficiency in statistical analysis and model validation techniques. A solid grasp of traditional and advanced modeling techniques and algorithms, such as Logistic Regression, Gradient Boosting, Random Forests, etc. * Expertise in model evaluation techniques such as ROC curves, precision-recall, KS, cross-validation, feature importance, SHAP values, etc. * Familiarity with regulatory requirements and guidelines related to risk model validation. * Strong communication and interpersonal skills; experience with Stakeholder management * Ability to work independently. Risk and control mindset: ability to ask incisive questions, assess materiality and escalate issues. * Ability to handle large volumes of transactional data. Familiarity with data extraction tools like Hive will be an advantage. * Successful candidate will have a demonstrable analytical problem solving, and the ability to deliver projects in a fast-paced environment. Willing to learn and can-do attitude.
Education & alternatives
Education: * Master’s/Bachelor’s degree in Statistics, Economics, Finance, Mathematics or a related quantitative field; Engineering/MBA background from a premier institute This job description provides a high-level review of the types of work performed. Other job-related duties may be assigned as required.
Tools in this posting
- Python
- SAS
- SQL
- Hive
- Spark
Source — Tool mentions in context
Qualifications: * 3+ years of hands-on analytical experience * 2+ years’ experience in statistical analysis with working knowledge of at least one of the following statistical software packages: Python (Must), Hive, Spark, SAS * Strong quantitative, analytical, and problem-solving skills; knowledge of probability theory, statistics, mathematical finance, econometrics, numerical methods * Strong understanding of statistical concepts and modelling techniques including traditional and advanced ML algorithms * Strong proficiency in statistical analysis and model validation techniques. A solid grasp of traditional and advanced modeling techniques and algorithms, such as Logistic Regression, Gradient Boosting, Random Forests, etc. * Expertise in model evaluation techniques such as ROC curves, precision-recall, KS, cross-validation, feature importance, SHAP values, etc. * Familiarity with regulatory requirements and guidelines related to risk model validation. * Strong communication and interpersonal skills; experience with Stakeholder management * Ability to work independently. Risk and control mindset: ability to ask incisive questions, assess materiality and escalate issues. * Ability to handle large volumes of transactional data. Familiarity with data extraction tools like Hive will be an advantage. * Successful candidate will have a demonstrable analytical problem solving, and the ability to deliver projects in a fast-paced environment. Willing to learn and can-do attitude. Education:
Partner closely with Strategy partners and Model Risk Management validators across the model lifecycle including validation, ongoing performance evaluation, and annual reviews. * Responsible for model development, validation and testing of fraud detection models, including statistical analysis, data validation and model performance evaluation. * Conduct rigorous validation assessment for fraud model validation; develop and implement validation methodologies to assess model accuracy, robustness, and effectiveness. * Ensure compliance with regulatory requirements and industry best practices in fraud detection and model validation. * Incumbents work with large and complex data sets (both internal and external data) to evaluate, recommend, and support the implementation of business strategies. * Identifies and compiles data sets using a variety of tools (e.g. Hive, SQL) to help predict, improve, and measure the success of key business to business outcomes * Responsible for documenting data requirements, data collection / processing / cleaning, and exploratory data analysis, which may include utilizing statistical models / algorithms and data visualization technique. * Appropriately assess risk when business decisions are made, demonstrating particular consideration for the firm's reputation and safeguarding Citigroup, its clients and assets, by driving compliance with applicable laws, rules and regulations, adhering to Policy, applying sound ethical judgment regarding personal behavior, conduct and business practices, and escalating, managing and reporting control issues with transparency. Qualifications:
Posting record
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- First seen by us
- Oct 18, 2026 · today
- Recorded sightings
- 1
- Employer says posted
- Oct 14, 2026
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Bengaluru, KA, IN
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