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Senior Analyst, Advanced Analytics

Full-time

Liberty Mutual Insurance

Role Description

We’re looking for an experienced, stakeholder-focused analyst to join our USRM Fraud Hub Analytics team. In this high-visibility, high-impact role, you will be using data-driven insights to advance fraud detection and prevention for the Internal Sales and Service Fraud domain. This role is a great fit for someone who enjoys working directly with stakeholders, digging into messy data, and turning ambiguous requests into insights.

In this role, you'll work closely with the Central Fraud Hub leadership team and the Analytics Asst Director to:

  • Expand analytics capabilities in the Internal Sales and Service Fraud space.
  • Identify new opportunities for lead generation.
  • Deliver timely insights that influence business decisions.

Your work will directly support the Central Fraud Hub's efforts to:

  • Detect and prevent fraud.
  • Improve investigator efficiency.
  • Help protect USRM's profitability as the business continues to grow.

Key Responsibilities

  • Dedicate 80% of your time developing, coding, and testing fraud scenarios to generate efficacious leads for the Internal Sales and Service Fraud Investigation team using advanced data analysis techniques and tools (e.g. Snowflake, SQL, SAS, PowerBI, etc.).
  • Directly support our Internal Sales and Service Fraud Investigation stakeholders by leveraging marketing, distribution, and call data to identify suspicious patterns, anomalies, and emerging fraud trends across lines of business; including ad hoc requests to support active and future investigations.
  • Partner with Fraud Hub leaders on strategic priorities and collaborate with Data Science and Reporting partners to integrate your insights into impactful dashboards and modeling solutions.
  • Support the Analytics Asst Director to refine and update the framework that defines how we value potential Internal Sales and Service fraud leads.
  • Develop operational health metrics and deliver data-driven narratives for the monthly operational review (MOR), surfacing performance drivers and improvement opportunities.
  • Define best-in-class standards for fraud analytics excellence, institutionalize domain-specific business and technical expertise, and drive “build-once-reuse-many” framework.

Qualifications

  • Bachelor's Degree plus a minimum 3 years, typically 4 or more years of experience, or equivalent, is required.
  • Mathematics, Economics, Statistics or other quantitative field are preferred fields of study.
  • Advanced knowledge of data sources, tools, statistical principles and methodologies, and techniques.
  • Advanced proficiency in Excel (VBA, macros, scripts, formulas, data visualization, etc.), PowerPoint, and statistical software packages (SAS, Emblem).
  • Must have good planning, analytical, decision-making and communication skills. Solid understanding of business to improve business outcomes.

Requirements

  • Experience with Internal Sales and Service data is a strong plus (or experience with financial fraud).
  • Strong technical and analytical skills, experience working with large datasets and advanced coding techniques (preferably SQL).
  • Strong stakeholder orientation: able to actively listen to and understand the stakeholder’s needs; understand the stakeholder’s end goal so you can deliver data and analyses that are usable and timely.
  • Proven ability to successfully tackle high complexity analysis with minimal direction.
  • Think critically and holistically about the data and analysis that will best serve our stakeholders.
  • Manage and set expectations proactively and independently across multiple workstreams.
  • Possess subject matter expertise in your domain and the ability to tell compelling stories with data.
  • Champion continuous improvement by developing resources and institutionalizing knowledge.

Benefits

  • Comprehensive benefits.
  • Workplace flexibility.
  • Professional development opportunities.
  • Opportunities provided through Employee Resource Groups.
Vacancy posted 1 day ago
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