Develop strategies, manage resources, lead team meetings, and monitor performance metrics.
Responsibilities- Build predictive models for real-time fraud detection systems.
- Evaluate and optimize existing ML models for performance, scalability, and explainability.
- Apply deep learning and advanced analytics for behavior analysis and risk profiling.
- Analyze transaction data to identify patterns, anomalies, and fraud trends.
- Perform exploratory data analysis (EDA) to understand customer behavior and potential fraud vulnerabilities.
- Translate data-driven insights into actionable recommendations for leadership and stakeholders.
- Collaborate with fraud strategy and operations teams to enhance fraud prevention frameworks.
- Validate and monitor predictive models for real-time fraud detection systems using valid monitoring metrics/KPI’s.
- Prepare technical documents related to fraud models and model validation. Validate the models using various techniques and KPIs, out of time validation etc.
- Set up monthly/quarterly and annual monitoring for the models using valid monitoring metrics/KPI’s.
- Perform Root Cause Analysis in case of deterioration of model performance/data issues.
- Evaluate and optimize existing ML models for performance, scalability, and explainability.
- Apply deep learning and advanced analytics for behavior analysis and risk profiling as part of
- Analyze transaction data to identify patterns, anomalies, and fraud trends.
- Perform exploratory data analysis (EDA) to understand customer behavior and potential fraud.
- Translate data-driven insights into actionable recommendations for leadership and stakeholders.
- Collaborate with other teams like fraud strategy to enhance fraud prevention frameworks.
- 3-5+ years of experience in analytics preferably in Banking and Financial Services
- A minimum of 3 years of hands-on experience working on monitoring and validation of Machine Learning models to solve analytical use cases.
- Solid understanding of banking products, fraud types (e.g., account takeover, synthetic fraud, identity theft), and transaction systems.
- Knowledge of various statistical techniques used in analytics (regression, ML Models, Monitoring Metrics like KS, PSI, CSI, MAPE, Confusion Metrics etc.)
- Excellent problem-solving and analytical skills, with the ability to work on complex projects and deliver high-quality results.
- Proficiency in programming languages such as Python, and experience with ML related libraries.
- Experience with large-scale data processing and distributed computing frameworks is a plus.
- Strong communication skills, both written and verbal, with the ability to convey complex ideas to diverse stakeholders.
Skills Required
- 3-5+ years of experience in analytics, preferably in Banking and Financial Services
- Minimum of 3 years hands-on experience monitoring and validating Machine Learning models
- Solid understanding of banking products, fraud types (account takeover, synthetic fraud, identity theft), and transaction systems
- Knowledge of statistical techniques and monitoring metrics (regression, ML models, KS, PSI, CSI, MAPE, confusion metrics)
- Proficiency in Python and experience with ML libraries
- Experience with large-scale data processing and distributed computing frameworks
- Excellent problem-solving and analytical skills
- Strong written and verbal communication skills to convey complex ideas to stakeholders
- Experience setting up and maintaining model monitoring, KPIs and producing technical documentation for model validation
What We Do
Choosing a digital partner is about more than capabilities — it’s about collaboration and character. Unrealistic overhauls and off-the-shelf products ignore what matters most — your unique needs, culture, goals, and your legacy data and technology environments. At EXL, our collaboration is built on ongoing listening and learning to adapt our methodologies. We’re your business evolution partner—tailoring solutions that make the most of data to make better business decisions and drive more intelligence into your increasingly digital operations. Whether your goals are scaling the use of AI and digital, redesign operating models, or driving better and faster decisions, we’re here to partner with you to help you gain—and maintain—competitive advantage with efficient, sustainable models at scale. Our expertise in transformation, data science, and change management helps make your business more efficient and effective, improve customer relationships and enhance revenue growth. Instead of focusing on multi-year, resource- and time-intensive platform designs or migrations, we look deeper at your entire value chain to integrate strategies with impact. We use our specialization in analytics, digital interventions, and operations management—alongside deep industry expertise — to deliver solutions that help you outperform the competition. At EXL, it’s all about outcomes—your outcomes—and delivering success on your terms. Share your goals with us and together, we’ll optimize how you leverage data to drive your business forward. For more information, visit www.exlservice.com.
