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Remote Insurance Data Analytics Jobs in Philadelphia, PA

Berkadia

Senior Financial Analyst- Remote

Philadelphia, PA · Remote

$86K - $107K/yr

Skilled in data analytics, including demographics, competitors, and industry trends. Ability to ... Pet insurance discounts * And more! Be the Next Big Thing. Be Berkadia. #LI-HB1 #LI-REMOTE

Comcast

Senior Compliance Analyst

Philadelphia, PA · On-site +1

... remote option.) Job Summary Job Summary We are seeking a highly analytical and technically ... You will leverage data analytics and automated monitoring tools to assess control effectiveness ...

Milliman

Strategic Data Partnership Manager

Berwyn, PA · Remote

Over 300 leading healthcare organizations have come to rely on MedInsight analytic solutions for ... This position is fully remote, while occasional travel may be required. Primary Responsibilities:

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All JobsInsurance Data Analytics JobsRemote Insurance Data Analytics JobsRemote Insurance Data Analytics Jobs in Philadelphia, PA

Remote Insurance Data Analytics information

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$24

$55

$95

How much do remote insurance data analytics jobs pay per hour?

As of Sep 4, 2026, the average hourly pay for remote insurance data analytics in Philadelphia, PA is $55.24, according to ZipRecruiter salary data. Most workers in this role earn between $44.38 and $62.60 per hour, depending on experience, location, and employer.

What is remote insurance data analytics?

Remote insurance data analytics is the practice of analyzing insurance-related data, such as claims, risk assessments, and customer information, from a location outside of a traditional office setting. Professionals in this field use statistical methods, data mining, and machine learning tools to identify patterns, detect fraud, and help insurance companies make data-driven decisions. This remote role often requires proficiency in data analysis tools like SQL, Python, or R, and a strong understanding of insurance industry concepts. Remote insurance data analysts collaborate with teams virtually to provide insights and support business strategies, making it a flexible career option.

What are the key skills and qualifications needed to thrive as a remote insurance data analytics professional?

To excel in Remote Insurance Data Analytics, you need strong analytical skills, a background in statistics or mathematics, and typically a degree in data science, actuarial science, or a related field. Familiarity with data analysis tools like SQL, Python, R, and specialized insurance analytics platforms such as SAS or Tableau, as well as relevant certifications, is highly valuable. Attention to detail, problem-solving abilities, and effective communication set candidates apart in this role. These skills are crucial for transforming complex insurance data into actionable insights that drive informed business decisions and risk assessments.

How do remote insurance data analytics professionals typically collaborate with cross-functional teams to drive business insights?

Remote Insurance Data Analytics professionals often work closely with underwriters, actuaries, claims managers, and IT teams to gather data requirements, interpret findings, and implement data-driven solutions. Collaboration usually happens through virtual meetings, collaborative dashboards, and project management tools to ensure clear communication and alignment on objectives. This cross-functional approach helps identify trends, optimize risk assessments, and support strategic decision-making within the organization. Building strong relationships with team members across departments is key to successfully translating analytical results into actionable business strategies.

What is the difference between Remote Insurance Data Analytics vs Remote Insurance Underwriter?

AspectRemote Insurance Data AnalyticsRemote Insurance Underwriter
Required CredentialsBachelor's in Data Science, Statistics, or related field; often certifications in data analysis or analyticsBachelor's in Business, Finance, or related; often requires insurance licensing or certifications
Work EnvironmentPrimarily data analysis, modeling, and reporting; often collaborative with IT and actuarial teamsAssessing risks, reviewing applications, making underwriting decisions; involves communication with agents and clients
Employer & Industry UsageUsed across insurance companies, reinsurers, and brokers for data-driven decision makingUsed by insurance carriers to evaluate and approve policies

Remote Insurance Data Analytics focuses on analyzing insurance data to inform business decisions, while Remote Insurance Underwriters evaluate individual insurance applications to determine coverage. Both roles are essential in the insurance industry but differ in daily tasks and required skills.

What are the most commonly searched types of Insurance Data Analytics jobs in Philadelphia, PA?

The most popular types of Insurance Data Analytics jobs in Philadelphia, PA are:

What are popular job titles related to Remote Insurance Data Analytics jobs in Philadelphia, PA?

For Remote Insurance Data Analytics jobs in Philadelphia, PA, the most frequently searched job titles are:

What job categories do people searching Remote Insurance Data Analytics jobs in Philadelphia, PA look for?

The top searched job categories for Remote Insurance Data Analytics jobs in Philadelphia, PA are:

What cities near Philadelphia, PA are hiring for Remote Insurance Data Analytics jobs?

Cities near Philadelphia, PA with the most Remote Insurance Data Analytics job openings:

Remote Insurance Data Analytics jobs near you
Infographic showing various Remote Insurance Data Analytics job openings in Philadelphia, PA as of August 2026, with employment types broken down into 57% Full Time, and 43% Contract. Highlights an 100% Remote job distribution, with an average salary of $114,908 per year, or $55.2 per hour.

Senior Director, Marketing Data Strategy (Remote)

Forbes Advisor

Wilmington, DE • On-site, Remote

Full-time

This job post has expired 2 days ago. Applications are no longer accepted.

Job description

At Forbes Advisor, our mission is to help readers turn their aspirations into reality. We arm people with trusted advice and guidance so they can make informed decisions they feel confident in and get back to doing the things they care about most.
We are an experienced team of industry experts dedicated to helping readers make smart decisions and choose the right products with ease. Forbes Advisor boasts decades of experience across dozens of geographies and teams, including Content, SEO, Business Intelligence, Finance, HR, Marketing, Production, Technology and Sales. The team brings rich industry knowledge to Forbes Advisor's global coverage of consumer credit, debt, health, home improvement, banking, investing, credit cards, small business, education, insurance, loans, real estate and travel.
We're looking for a leader who wants to help build the future of marketing data strategy at Forbes Digital Marketing. Our Data & Analytics organisation sits at the heart of our mission. We build the products, platforms and intelligence that power marketing, commercial decision making, customer understanding and revenue growth across the business. As we continue to invest in first-party data, machine learning, marketing technology and AI, we're looking for a senior leader to help define the next phase of that journey.
This is not a traditional data leadership role. Working directly with the VP of Data Strategy, you'll act as a trusted technical counterpart - bringing deep expertise, challenging thinking, and helping shape strategic decisions across our marketing data ecosystem. You'll join an established leadership team spanning Engineering, Analytics, Data Science and Operations, helping define how customer data, marketing measurement, attribution, analytics and AI come together to improve business performance. You'll also act as a senior technical counterpart to key technology partners, helping ensure our strategy evolves alongside the wider marketing ecosystem.
If you're motivated by solving complex commercial problems, challenging conventional thinking, building products rather than projects, and helping organisations use data more effectively, we'd love to hear from you.
Responsibilities:
  • Marketing Measurement & Attribution: Help define how we measure marketing performance across channels and ensure that our measurement strategy enables better commercial decisions.
  • Customer Intelligence & First-Party Data: Help shape how customer data is collected, organised and activated across the business.
  • Marketing Platforms & Activation: Ensure our marketing platforms receive the right data to optimise effectively and maximise commercial performance.
  • Data Products & Decision Intelligence: Help move the organisation from one-off analysis towards reusable products and decision-support capabilities.
  • Strategic Leadership: Challenge assumptions and influence the future direction of our marketing data strategy.
  • Team Leadership & Capability Building: Play an important role in building and developing the next generation of leaders across Data & Analytics.

Requirements:
We're deliberately not looking for someone who has done everything. Instead, you'll bring deep expertise in one or more of our strategic domains together with the ability to collaborate across the wider marketing data ecosystem.
You'll likely bring:
  • Experience leading strategic marketing data, customer intelligence, analytics or data product initiatives that delivered measurable business outcomes.
  • Deep expertise in at least one of the following:
  • Marketing measurement and attribution
  • Customer intelligence and first-party data
  • Applied data science and predictive modelling
  • Marketing platforms and activation
  • Data products and decision intelligence
  • A track record of building products, platforms or capabilities that deliver measurable commercial outcomes.
  • Deep understanding of Performance Marketing
  • Strong commercial judgement and the ability to prioritise initiatives based on business value.
  • Confidence influencing senior stakeholders across both technical and non-technical audiences.
  • Experience developing teams, coaching leaders and building organisational capability.
  • Curiosity about emerging technologies - particularly AI - and a pragmatic approach to applying them where they create genuine business value.

Forbes Advisor provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.
#LI-REMOTE #LI-NM1

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