Fraud Analytics at Principal Financial Services, Inc.

Hyderabad, Telangana, India -

Full Time

Start Date

Immediate

Expiry Date

22 Jun, 26

Salary

0.0

Posted On

24 Mar, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Extraction, Data Analysis, Machine Learning, Predictive Modeling, Quantitative Methods, Reporting, Fraud Investigations, Data Science, Power BI, Model Validation, Data Quality, Data Lineage, Data Security, Compliance, Data Warehousing, Data Lakes

Industry

Financial Services

Description

Responsibilities Fraud Analytics Individual Contributor Job Purpose This role combines investigative expertise with advanced analytic capabilities and data science, including data extraction and analysis, machine learning, predictive modeling, quantitative methods, and modern reporting. You will collaborate with the Corporate Special Investigations Unit (“CSIU”) team to drive data-driven fraud analysis and modeling across the descriptive, diagnostic, predictive, and prescriptive continuum. This involves not only creating information that can drive or support complex fraud investigations, but also transforming insights gained into effective and efficient prevention, detection, and response strategies. You will support the CSIU leadership team in its efforts and you will lead enterprise fraud and investigative data-driven reporting processes. Leadership at Principal As a leader at Principal, you’re responsible for activating our strategy, meeting evolving customer needs, and crafting an inclusive culture. Our leadership expectations serve as a guide to the standards encouraged from all our leaders. Our leaders need to be a positive brand ambassador of our core values and purpose. They need to understand our code of conduct and know the responsibility to comply. They stay respectful of diversity and differences and work towards building inclusive teams and partnerships. Key Responsibilities Enterprise Investigative Analytics Serve as the CSIU’s primary data science architect and technical analyst for fraud data in cases of suspected unethical or fraudulent activity throughout the enterprise. Extract and deliver comprehensive evidence and data for large, high-risk, or complex investigations. Subject Matter Point Peron Collaborate closely with other internal stakeholders to understand, leverage, and influence utilization of existing fraud analytic tools. During exploration of new fraud prevention, detection, or investigative tools, act as the primary evaluative resource/external vendor liaison for the CSIU. Drive ongoing results that benefit the CSIU and other internal stakeholders. Data Extraction Extract and consolidate data from Principal systems into structured, consumable formats for analysis. Integrate cross-system data (e.g., claims, payments, customer, policy, access logs, case management) to build comprehensive investigative views. Evaluate and recommend internal/external data sources, coordinate with data owners, platform teams, and governance partners. Apply robust data quality, lineage, security, and compliance practices in governed environments (data warehouses/lakes; cloud). Fraud Analytics Translate investigative hypotheses into understandable analytic frameworks; quantify impact and manage false positive/negative tradeoffs. Apply machine learning, predictive modeling, and quantitative techniques to solve complex business problems. Act as the subject matter expert on innovative analytic methods; create design requirements, set project timelines, and drive superior technical solutions. Manage multiple projects across the analytics continuum (descriptive, diagnostic, predictive, prescriptive); ensure disciplined delivery and measurable impact. Apply emerging analytic principles and techniques to support business decisions and investigative strategies. Lead model development and validation end-to-end, including diagnostics and monitoring. Develop processes and metrics to monitor model performance; recommend refits/enhancements to maintain efficacy and manage risk. Fraud Reporting Design and deliver executive-ready dashboards and visualizations using Power BI (expert level); enable secure self-service where appropriate. Build easy to understand data visualization products to support complex investigations, particularly when there are groups of threat actors involved. Build automated reporting for fraud metrics, case pipelines, operational KPIs, and model performance; communicate trends to business partners. Present complex findings clearly to nontechnical stakeholders and regulators; create concise executive summaries and regulatory-ready materials. Qualifications Graduate

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Responsibilities

This role involves combining investigative expertise with advanced analytics, data science, and machine learning to drive data-driven fraud analysis and modeling across descriptive, diagnostic, predictive, and prescriptive stages. Key duties include extracting evidence for complex investigations and transforming insights into effective prevention, detection, and response strategies.