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Insurance Data Analytics Jobs in Austin, TX (NOW HIRING)

Hippo Insurance

Data Analyst

Austin, TX · On-site

Insurance, healthcare, or regulated industry experience * Familiarity with HR or operations analytics * Exposure to data governance or compliance reporting * Proven experience leveraging AI to ...

Hippo Insurance

Data Analyst

Austin, TX · On-site

Insurance, healthcare, or regulated industry experience * Familiarity with HR or operations analytics * Exposure to data governance or compliance reporting * Proven experience leveraging AI to ...

Pwc

Finance Data, Analytics & AI - Associate

Austin, TX · On-site

$61K - $100K/yr

... Insurance, Science - Utilizing Business Intelligence and Reporting Tools (BIRT) for data-driven ... analysis and interpretation - Engaging in stakeholder management and competitive advantage ...

Ci

Data Analyst

Austin, TX · On-site

Ad-hoc analytics and insights . Promptly address ad-hoc analysis requests with clear, well ... Employer paid Dental, Vision & Life and AD&D Insurance * Employer paid Short-term & Long-term ...

FALL CREEK FARM & NURSERY

Data Analyst

Austin, TX · On-site

$5.4K - $8.8K/mo

Our comprehensive benefits package includes 100% paid employee health insurance for full-time ... The ideal candidate will possess a strong foundation in data analytics, reporting, and statistical ...

TrendMicro

Marketing Data & Analytics Lead

Austin, TX · On-site

... data teams on a shared analytics platform, and enough technical fluency to specify work precisely ... Life insurance * Short & Long Term Disability * Pre-partum, maternity, parental and medical leave

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Insurance Data Analytics information

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How much do insurance data analytics jobs pay per hour?

As of Sep 11, 2026, the average hourly pay for insurance data analytics in Austin, TX is $54.27, according to ZipRecruiter salary data. Most workers in this role earn between $43.61 and $61.49 per hour, depending on experience, location, and employer.

What is insurance data analytics?

An Insurance Data Analytics job involves analyzing large volumes of insurance-related data to identify trends, assess risks, detect fraud, and improve decision-making. Professionals in this field use statistical models, machine learning, and data visualization tools to extract insights that help insurers optimize pricing, enhance customer experience, and reduce losses. They work with claims data, policyholder information, and external data sources to drive business strategy. Strong analytical skills, proficiency in data tools like SQL, Python, or R, and knowledge of insurance principles are essential for success in this role.

What are the typical responsibilities of someone working in insurance data analytics?

Professionals in Insurance Data Analytics are responsible for collecting, cleaning, and analyzing large sets of insurance-related data to identify trends, assess risk, and inform business decisions. They commonly develop predictive models, generate reports, and provide actionable insights that help underwriting teams, actuarial staff, and business leaders optimize processes or pricing strategies. Day-to-day tasks may also include collaborating with IT and business units to define data requirements, presenting findings to non-technical stakeholders, and ensuring data integrity. This role often involves a mix of independent analysis and team-oriented projects, offering a dynamic and engaging work environment for problem solvers.

What are the key skills and qualifications needed to thrive in insurance data analytics?

To thrive in Insurance Data Analytics, you need a solid understanding of data analysis, statistics, and insurance industry concepts, usually supported by a degree in mathematics, statistics, finance, or a related field. Proficiency with analytical tools like SQL, Python, R, and data visualization platforms (such as Tableau or Power BI), as well as certifications like CPCU or advanced analytics credentials, are highly valued. Strong problem-solving abilities, attention to detail, and effective communication skills help analysts translate complex data into actionable business insights. These skills are crucial for driving informed decision-making, risk assessment, and operational improvements within insurance organizations.

How is data analytics used in insurance?

In insurance, data analytics is used by professionals to assess risk, set premiums, detect fraud, and improve customer segmentation. Analysts utilize tools like statistical models and machine learning algorithms to interpret large datasets, enabling more accurate underwriting and claims management. Strong analytical skills and knowledge of data visualization are essential for effective decision-making in this field.

What does a data analyst do in insurance?

An insurance data analyst examines large datasets to identify trends, assess risk, and support decision-making processes within insurance companies. They use tools like Excel, SQL, and data visualization software to interpret claims, policy data, and customer information, helping improve underwriting, pricing, and fraud detection.

What are the most commonly searched types of Insurance Data Analytics jobs in Austin, TX?

The most popular types of Insurance Data Analytics jobs in Austin, TX are:

What are popular job titles related to Insurance Data Analytics jobs in Austin, TX?

For Insurance Data Analytics jobs in Austin, TX, the most frequently searched job titles are:

What job categories do people searching Insurance Data Analytics jobs in Austin, TX look for?

The top searched job categories for Insurance Data Analytics jobs in Austin, TX are:

What cities near Austin, TX are hiring for Insurance Data Analytics jobs?

Cities near Austin, TX with the most Insurance Data Analytics job openings:

Insurance Data Analytics jobs near you
Infographic showing various Insurance Data Analytics job openings in Austin, TX as of September 2026, with employment types broken down into 1% As Needed, 73% Full Time, 21% Part Time, and 5% Contract. Highlights an 88% Physical, 1% Hybrid, and 11% Remote job distribution, with an average salary of $112,872 per year, or $54.3 per hour.

VP/Delivery Lead - Banking, Financial Services & Insurance (Data, Analytics, AI & Integration)

Austin, TX • On-site

Persistent Systems
Software Development • 51 - 200 employees
Learn more about Persistent Systemsexternal

Other

This job post has expired 1 day ago. Applications are no longer accepted.

Job description

About Persistent:



We are an AI-led, platform-driven Digital Engineering and Enterprise Modernization partner, combining deep technical expertise and industry experience to help our clients anticipate what’s next. Our offerings and proven solutions create a unique competitive advantage for our clients by giving them the power to see beyond and rise above. We work with many industry-leading organizations across the world, including 20 Fortune 50 companies and 4 of the 5 top banks in both the US and India, and numerous innovators across the healthcare ecosystem


Our disruptor’s mindset, commitment to client success, and agility to thrive in the dynamic environment have enabled us to sustain our growth momentum. Persistent has been recognized across top industry platforms for innovation, leadership, and inclusion. We have delivered 24 sequential quarters of growth with $436.5M in Q4 FY26 revenue, up 17.4% Y-o-Y growth. Our 26,500+ global team members, located in 18 countries, have been instrumental in helping the market leaders transform their industries. We won the 2025 ISG Star of Excellence™ Award for AI and Data Excellence and were named a Leader in the Everest Group Talent Readiness for Next-generation Data, Analytics and AI Services PEAK Matrix® Assessment 2025.


Role: Vice President/Delivery Lead– Banking, Financial Services & Insurance (Data, Analytics, AI & Integration)

Location: Austin, Texas

Experience: 18–25 Years


Role Overview

Persistent is seeking a seasoned Delivery Lead to lead our Banking, Financial Services & Insurance (BFSI) Data, Analytics, AI & Integration practice. This executive will drive strategic customer engagements, large-scale cloud and AI transformation programs, delivery excellence, and business growth across key BFSI accounts.


Key Responsibilities

  • Lead end-to-end delivery for strateg3ic BFSI Data, Analytics, AI, and Integration engagements.
  • Drive enterprise data modernization and legacy-to-cloud transformations using modern data platforms.
  • Own delivery governance, customer satisfaction, financial performance, and operational excellence.
  • Build trusted advisor relationships with CIOs, CDOs, CTOs, and business stakeholders.
  • Partner with Sales and Consulting to shape large deals, support pursuits, and drive account growth.
  • Lead and mentor global teams of delivery managers, architects, and engineering leaders.
  • Foster an engineering-first culture focused on innovation, automation, DataOps/MLOps, AI adoption, and reusable accelerators.
  • Drive continuous improvement, talent development, and delivery best practices across the practice.


Required Experience

  • 18–25 years of experience in IT Services, Digital Engineering, or Consulting.
  • Bachelor's degree in Engineering, Computer Science, or a related technical discipline from a reputed institution; Master's degree preferred.
  • Proven success leading large-scale Data, Analytics, AI, and Integration programs for Banking, Financial Services & Insurance (BFSI) clients.
  • Strong experience managing multi-million-dollar delivery portfolios and distributed global teams.
  • Demonstrated ability to drive customer success, operational excellence, and profitable growth.


Technical & Domain Expertise

  • Modern Data Platforms: Snowflake, Databricks, Microsoft Fabric, Azure Synapse.
  • Cloud Platforms: Azure, AWS, and/or Google Cloud.
  • Data Engineering: Spark, Python, SQL, ETL/ELT, Lakehouse architecture, DataOps.
  • AI & Analytics: Machine Learning, Generative AI, LLM-enabled solutions, Power BI, Tableau.
  • Integration: API-led architectures, MuleSoft, Kafka, Azure Integration Services.
  • Strong understanding of BFSI data ecosystems, financial services architecture, regulatory requirements, risk management, security, governance, and compliance (e.g., PCI DSS, SOX, AML/KYC, BCBS 239, GDPR, or equivalent).


Ideal Candidate

  • Engineering-led delivery executive with a passion for solving complex business problems through technology.
  • Proven experience leading enterprise data transformation to cloud-native platforms such as Snowflake and Databricks.
  • Strong executive presence with the ability to influence C-suite stakeholders and build long-term strategic partnerships.
  • Growth-oriented leader with a track record of scaling teams, developing talent, and expanding strategic client relationships.
  • Passionate about leveraging AI and modern engineering practices to deliver measurable business outcomes for Banking, Financial Services & Insurance (BFSI) clients.


Success Metrics

  • Customer satisfaction (CSAT/NPS)
  • Delivery predictability and quality
  • Revenue growth and account expansion
  • Gross margin improvement
  • Successful cloud and AI transformation outcomes
  • Team engagement and retention
  • Reusable engineering assets and automation adoption
  • Delivery governance and compliance



Our company fosters a values-driven and people-centric work environment that enables our employees to:


  • Accelerate growth, both professionally and personally.
  • Impact the world in powerful, positive ways, using the latest technologies.
  • Enjoy collaborative innovation, with diversity and work-life wellbeing at the core.
  • Unlock global opportunities to work and learn with the industry’s best.

Apply