Data Scientist – Fraud & Scams Detection

What impact will you make? Every day, your work will make an impact that matters, while you thrive in a dynamic culture of inclusion, collaboration and high performance. As the undisputed leader in professional services, Deloitte is where you will find unrivaled opportunities to succeed and realize your full potential Deloitte is where you will find unrivaled opportunities to succeed and realize your full potential. The Team Deloitte’s practice can help you uncover and unlock the value buried deep inside vast amounts of data. Our global network provides strategic guidance and implementation services to help companies manage data from disparate sources and convert it into accurate, actionable information that can support fact-driven decision-making and generate an insight-driven advantage. Our practice addresses the continuum of opportunities in business intelligence & visualization, data management, performance management and next-generation analytics and technologies, including big data, cloud, cognitive and machine learnin g. Learn more about Analytics and Information Management Prac tice Position Title: Data Scientist – Fraud & Scams Detection Role Type: Data Scientist / Model Developer Division: Division or Business Unit, e.g., Financial Crime Analytics / Technology & Operations Role Purpose: - The Data Scientist – Fraud & Scams Detection will be responsible for designing, developing, and deploying advanced machine learning models to detect and mitigate fraud in digital and card transactions. This role supports the transition from a third-party solution to an internally developed and managed fraud detection system. The successful candidate will play a key role across the full model lifecycle—from early-stage analysis and feature engineering through to deployment and post-production monitoring working closely within an agile squad environment. Key Responsibilities Design and develop fraud and scams detection models tailored to digital and card transaction data. Replace existing third-party fraud detection solutions with internally developed models. Define and test different ML approaches suitable for the fraud domain. Lead feature engineering, feature selection, and hyperparameter tuning for model optimization. Collaborate with business stakeholders, engineers, and squad members from initial discovery to deployment. Articulate design choices, modeling approaches, and monitoring strategies clearly and effectively. Deploy models into production using modern MLOps practices. Maintain model accuracy, relevance, and compliance through ongoing monitoring and evaluation. Key Performance Indicators (KPIs) Successful deployment of fraud detection models with measurable accuracy and performance. Reduction in false positives/negatives relative to the third-party benchmark. Timely delivery of model milestones aligned to project timelines. Evidence of collaboration and active contribution in agile squad setup. Quality and robustness of documentation and monitoring processes. Essential Experience Proven experience in developing and deploying fraud detection or risk models in production environments. Experience with end-to-end model development, including: Algorithm selection Feature engineering and selection Model training and tuning Deployment and post-deployment monitoring Strong understanding of fraud patterns and digital transaction behaviors. Hands-on experience working within agile teams or squads on data science delivery. Technical & Functional Competencies Required: High proficiency in SQL , Python , PySpark Strong understanding of version control using Git Preferred: Experience with Databricks Familiarity with MLOps frameworks and production workflows Soft Skills & Attributes Analytical mindset with a strong problem-solving approach. Ability to articulate complex data science concepts and decisions to non-technical stakeholders. Proactive, self-driven, and accountable for delivering high-quality outcomes. Strong communication and collaboration skills. Comfortable working in fast-paced, evolving environments. Qualification Requirements Bachelor's or postgraduate degree in Computer Science , Statistics , Mathematics , Engineering , or a related quantitative field. Our purpose Deloitte is led by a purpose: To make an impact tha t matters. Every day, Deloitte people are making a real impact in the places they live and work. We pride ourselves on doing not only what is good for clients, but also what is good for our people and the Communities in which we live and work—always striving to be an organization that is held up as a role model of quality, integrity, and positi ve change. Learn more about Deloitte's impact o n the world

Location: in, IN

Posted Date: 6/18/2025