Senior Fraud Analytics Analyst

As a Senior Fraud Analytics Analyst on the Fraud Data Team, you will be directly responsible for identifying potential fraud risk at all applicable levels of data hierarchy.  You’ll enable safer claims processes for our users and help Assurant manage claim risk intelligently. This role requires a deep understanding of fraud concepts, the ability to support data pipelines, conduct statistical experiments, develop reports/dashboards for both internal and external audiences, and the ability to drive a broad set of projects independently. The role also requires the ability to work with cross-functional teams (operations, finance, legal, customer experience, data sciences, data engineering, etc.) to influence and execute on fraud risk strategies.

What are the requirements need for this position?

Fraud Risk Analysis

• Leverage external and internal data to come up with insights to develop best in class fraud policies that will create value for Assurant and its customers.
• Work with large data sets to solve problems that could be ambiguous and nuanced using a variety of analytical and statistical approaches.
• Regularly collaborate with other SMEs and decision-makers to develop data-driven policies, processes, and models to improve overall fraud risk mitigation strategy.
• Develop dashboards, analytical frameworks, and detailed reporting models that provide reliable, easily digestible insights to key stakeholders to help guide decisions around process, policy, and system configuration.

Data Management

• Deploy modern data management tools to curate our most important data sets, models, and processes, while identifying areas for process automation and further efficiencies.
• Develop and Maintain data pipelines in support of various reporting, modeling, and machine learning initiatives.
• Evaluate, select, and acquire new internal & external data sets that contribute to business decision-making.
• Maintain accuracy within all data sets utilized in all reporting and analytical processes performed by the Fraud Data Team.

Analyze and Configure Integrated Risk Environments

• Develop and maintain ongoing analyses specific to integrated fraud solutions deployed within the Assurant fraud ecosystem (e.g.: Identity, Payments, GRM, etc.)
• Drive configuration review discussions and apply changes as agreed upon by stakeholders.
• Take ownership of all data inputs and outputs related to assigned environment and maintain a data pipeline which can support the various data initiatives across the enterprise.

Process Engineering & Integration

• Work with internal partners like Engineering, Product, Data Science and Operations to develop solutions that would mitigate fraud risk across different lines of business, payment methods and products.
• Analyze existing processes or workflows using probability and statistics to optimize adaptive or corrective changes.
• Document existing and new fraud workflows with applicable metrics and measures.
• Liaison with appropriate areas to ensure applicable fixes/enhancements are implemented.

What are the requirements need for this position?

• Bachelor’s Degree in Computer Science, Statistics, or other related field or relevant work experience.
• 3+ years in Risk/Fraud.
• 3+ years’ experience in the analytics space, taking on progressively more complex work and senior roles.
• Proven track record of solving complex problems with an in-depth understanding of data, product, and business impact.
• Proficient working with at least one quantitative tools such as Python, R, or Stata.
• Expertise in data visualization tools (e.g., Looker, Tableau, Power BI).
• Advanced SQL is a must.
• Understanding of and exposure to workflow management tools (Airflow, SSIS, UC4).
• Strong ability to extract patterns and trends through the application of statistical techniques and hypothesis testing.
• Strong critical thinking skills and the ability to think outside the box.
• Organized and self-motivated individual, comfortable operating within ambiguity.
• Excellent communication skills, with the ability to explain complex analytical findings to non-technical stakeholders and comfortable speaking with senior/executive level leadership.
• Intellectually curious, data-driven, result-oriented, high in agility and has a high desire to learn and contribute.
• Experience with payment processing lifecycle and chargeback dispute process or working with machine learning and data science teams a plus.

Pay Range:

$62,000.00 - $103,400.00

Any posted pay range considers a wide range of compensation factors, including candidate backgroun