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Consultant, Advanced Analytics, Homeowners Operational Monitoring

Liberty Mutual

Liberty Mutual

Data Science
Boston, MA, USA
Posted on Mar 14, 2026

Consultant, Advanced Analytics, Homeowners Operational Monitoring

Job Locations US-Remote | US-WA-Seattle | US-MA-Boston | US-TX-Plano
ID
2026-74963
Position Type
Full-Time
Job Grade
16
Department
093A-05438 Property & Spec Analytics
Market
US Retail Markets
Referral Bonus Amount
1500
Minimum Salary
USD $83,000.00/Yr.
Maximum Salary
USD $176,000.00/Yr.
Typical Starting Salary
$100,000-$135,000
Recruiter
Jacqueline Stone
Internal Application Deadline
3/27/26

Description

The Homeowners Operational Monitoring team within US Retail Markets (USRM) Personal Lines (PL) Property & Specialty Analytics, Countrywide (CW) Analytics, is looking for a Consultant or Senior Analyst. The team is responsible for driving the right CW actions to achieve profitability then profitable growth by partnering broadly across USRM, monitoring internal and external information to find opportunities to improve business performance, and initiating and gaining buy-in on results of deep dives into key problems. The analyst will build out and maintain a monitoring framework to provide efficient, quick, meaningful and actionable insights to the organization in our pursuit to achieve our goals.

**This position may have in-office requirements based on candidate location.**

**This position may be hired at a Senior Analyst (G15) or Consultant (G16) level dependent upon candidate skills and experience at manager discretion.**

The successful candidate will have strong technical skills, the ability to turn data into meaningful qualitative insights, a strong capability to influence stakeholders, and the ability to drive their own work, take initiative, and use resources efficiently.

Responsibilities:

  • Monitor key growth and competitiveness metrics including detailed drivers such as new business vitality, bind mix among various customer segments, win rates and closure rates, and recommend improvements to monitoring as needed to support the business.
  • Pull, synthesize, and analyze data from various sources, and turn it into meaningful qualitative insights. Clearly and concisely communicate technical work to both technical and non-technical audiences.
  • Understand data sources and partner with data team to quickly identify and escalate data issues and improve upon data sources to further analytical capabilities.
  • Understand the impact of customer or funnel mix on our profitability or growth and determine how changes in mix could influence results, while considering impact of internal Underwriting or pricing decisions.
  • Model inclusiveness by living our values and contribute to creating an inclusive culture.
  • Provide guidance to less experienced employees.

Ideal candidate will have:

  • Strong working experience inside Property & Casualty Insurance; Homeowners experience desired.
  • Demonstrated knowledge of new business funnel metrics and ratios with proven track record of applying analytical insights to drive funnel efficiency.
  • Strong research, problem solving, analytical, critical thinking, influencing, relationship management, and presentation skills.
  • Ability to manage multiple competing priorities displayed through prior project management or equivalent experience.
  • Ability to query and navigate complex datasets using tools like SAS, Snowflake, SQL, or Python.

Qualifications

  • Bachelor's Degree plus a minimum 5 years, typically 7 or more years, of related experience required; Mathematics, Economics, Statistics or other quantitative field are preferred fields of study.
  • Master's Degree preferred; advanced education may be substituted for years of experience (Ph.D. with no professional experience).
  • Deep knowledge of data sources, tools and business drivers.
  • Ability to apply advanced analytical concepts to improve business outcomes.
  • Ability to build analytic tools that will be used by business teams to analyze results and opportunities.
  • Advanced proficiency in big data software packages (SAS, SQL, Snowflake, Python), Excel (VBA, macros, scripts, formulas, data visualization), and PowerPoint.
  • Must have good planning, analytical, decision-making and communication skills.
  • Ability to present data, visually and verbally, to guide conversations with business managers.

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