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Insurance Data Analytics Jobs in California (NOW HIRING)

True Classic

Data & Analytics Engineer

Calabasas, CA · On-site

$121K - $145K/yr

True Classic is hiring a Data & Analytics Engineer to partner in owning our data platform ... Company-paid medical, dental, and vision insurance * $100/month Health & Wellness stipend * Free ...

Ingram Micro

Principal, Data Analytics

Irvine, CA · On-site

$116K - $197K/yr

The Principal, Data Analytics will play a critical role in developing advanced analytical and ... life insurance, and wellbeing benefits, among others. This is not a complete listing of the job ...

Nature's Bakery

Sr. Data Analytics Manager

Pasadena, CA · On-site

Overview The Sr. Data Analytics Manager will play a pivotal role in shaping our sales and demand ... Medical, dental, and vision insurance offered for eligible employees * 401(k) plan with a company ...

Rivian

Durability Data Analytics Engineer

Irvine, CA

$96K - $120K/yr

As a Durability Data Analytics Engineer, you will be part of the collaborative team of simulation ... insurance, and long-term disability insurance to eligible employees. You may also have the ...

Rivian

Durability Data Analytics Engineer

Irvine, CA · On-site

$96K - $120K/yr

As a Durability Data Analytics Engineer, you will be part of the collaborative team of simulation ... insurance, and long-term disability insurance to eligible employees. You may also have the ...

Rivian

Durability Data Analytics Engineer

Irvine, CA · On-site

$96K - $120K/yr

As a Durability Data Analytics Engineer, you will be part of the collaborative team of simulation ... insurance, and long-term disability insurance to eligible employees. You may also have the ...

Ingrammicro

Principal, Data Analytics

Irvine, CA

$116K - $197K/yr

The Principal, Data Analytics will play a critical role in developing advanced analytical and ... life insurance, and wellbeing benefits, among others. This is not a complete listing of the job ...

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Insurance Data Analytics information

What are the key skills and qualifications needed to thrive in the Insurance Data Analytics position, and why are they important?

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.

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.

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 collects, processes, and analyzes insurance data to identify trends, assess risks, and support decision-making. They use tools like Excel, SQL, and data visualization software to create reports and models that improve underwriting, claims management, and pricing strategies.

How much does an insurance analyst make?

The average salary for an insurance analyst is around $65,000 to $85,000 per year, depending on experience, location, and industry. Entry-level roles typically start lower, while experienced analysts with specialized skills or certifications can earn higher salaries. Strong analytical skills and proficiency with data tools like Excel or SQL are often required.

Will AI replace a data analyst?

AI can automate routine data processing and analysis tasks, but the role of a data analyst, including those in insurance data analytics, involves interpreting complex data, providing insights, and making strategic decisions that require human judgment. Therefore, AI is more likely to augment rather than fully replace data analysts, who also need skills in data visualization, domain knowledge, and communication. Continuous learning and proficiency with analytics tools remain important for the role.

What is an Insurance Data Analytics job?

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 most commonly searched types of Insurance Data Analytics jobs in California? The most popular types of Insurance Data Analytics jobs in California are:
What are popular job titles related to Insurance Data Analytics jobs in California? For Insurance Data Analytics jobs in California, the most frequently searched job titles are:
What job categories do people searching Insurance Data Analytics jobs in California look for? The top searched job categories for Insurance Data Analytics jobs in California are:
What cities in California are hiring for Insurance Data Analytics jobs? Cities in California with the most Insurance Data Analytics job openings:
Insurance Data Analytics jobs near you
Infographic showing various Insurance Data Analytics job openings in California as of June 2026, with employment types broken down into 5% As Needed, 77% Full Time, 10% Part Time, 5% Temporary, and 3% Nights. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Data & Analytics Engineer

True Classic

Calabasas, CA • On-site

$121K - $145K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted yesterday

Job description

True Classic is hiring a Data & Analytics Engineer to partner in owning our data platform infrastructure and to serve as a key builder connecting our data warehouse to our AI, finance, and business stakeholder teams. This role will support core analytics engineering functions, ensuring clean, well-structured, and reliable data pipelines built to best practice standards.
This role is ideal for someone who is hands-on and technically rigorous, with a strong command of data engineering best practices - including pipeline design, data modeling, testing, and documentation - and can contribute meaningfully to a mid-build platform in a fast-paced, evolving environment.
All of True Classic's roles are global and omni-channel, leading designated areas of accountability across all product categories, countries, and sales and marketing channels. This role will have impact across DTC, retail, wholesale, marketplaces, and emerging channels, ensuring strategic alignment and executional rigor across the enterprise.
Areas of Accountability
Extend & Maintain the Data Platform
  • Build and maintain dbt models following best practices for modularity, testing, documentation, and code quality
  • Contribute to completion of open data model workstreams across inventory, media, and product functions
  • Expand data source connectivity and pipeline coverage across marketing and fulfillment systems
  • Maintain and improve ETL/ELT workflows via Daasity and BigQuery
  • Help monitor and optimize cloud data infrastructure for cost and performance
Bridge Data to the Business
  • Deploy and maintain Omni dashboards on top of BigQuery for cross-functional stakeholders
  • Support business KPI tracking by structuring financial data for forecasting, cost modeling, and channel-level P&L
  • Contribute to predictive models for demand forecasting, inventory planning, and revenue projections
  • Build and maintain the serving layer that the AI team queries - clean, modeled BigQuery tables in place of direct API calls
AI-Augmented Development
  • Use AI coding tools (Claude Code, Cursor, Copilot) daily to write dbt models, debug pipelines, and accelerate development
  • Collaborate with the AI team to ensure the warehouse serves their applications with clean inputs for automation, ML models, and real-time ops tools
  • Identify opportunities where AI can automate data quality checks, anomaly detection, and pipeline monitoring
Cross Functional Collaboration
  • Work with finance to ensure financial data structures support forecasting and P&L reporting needs
  • Partner with the AI team to ensure warehouse outputs support downstream automation and machine learning applications
  • Work alongside merchandising, operations, and analytics stakeholders to translate business questions into reliable data models and visualizations
Qualifications
  • 4+ years of experience in data engineering or analytics engineering
  • Strong understanding of data engineering best practices: pipeline design, data modeling, testing, and documentation
  • Hands-on experience with dbt Cloud, Google BigQuery, and SaaS API pipeline development
  • Strong SQL skills including joins, window functions, and CTEs
  • Python proficiency for pipeline scripting, API integrations, and light modeling
  • Familiarity with statistical modeling and predictive analytics (regression, time series)
  • Comfortable working with non-technical stakeholders to translate business questions into data models and visualizations
  • Proficiency with AI coding tools - daily use expected
Preferred Qualifications
  • NetSuite or ERP experience
  • Daasity, Shopify/Amazon data
  • Marketing attribution platforms (Meta CAPI, Google Ads, Triple Whale),
  • Omni/Looker, GitHub-based workflows
Workplace Arrangement
This role is on-site (5x week in office) based in Calabasas, CA.
Compensation and Benefits
Compensation
  • Competitive Salary + bonus
Time Off
  • Unlimited PTO and sick time
Health & Wellness
  • Company-paid medical, dental, and vision insurance
  • $100/month Health & Wellness stipend
  • Free Employee Assistance Program (EAP)
Work & Growth Support
  • $100/month Personal Workspace/Office stipend
Perks
  • $1,000/year True Classic merchandise allowance
  • 401(k) plan with 3% company match

True Classic is proud to be an equal opportunity employer. We celebrate and support differences in race, religion, color, national origin, gender, sexual orientation, gender identity, age, veteran status, and abilities. If you need assistance or accommodation due to a disability, please contact Human Resources.
At True Classic, our purpose is simple: empower everyone to look good and feel good.
Founded in 2019, we're a fast-growing apparel brand obsessed with fit, quality, and impact. But we're building more than great products-we're building a high-performance team where smart, driven people do meaningful work, move fast, and see the direct results of what they create.
Everything we do is guided by the True Classic Operating System (TCOS)-the principles that shape how we work, make decisions, and win together:
  • Move the Needle - Our #1 value and the ultimate filter for decision-making. We focus on delivering tangible, measurable results that drive real business impact.
  • Paint the Picture - We set clear vision and help others see what great looks like.
  • Seek the Truth - We use data, customer insight, and curiosity to guide decisions.
  • Get 1% Better - We continuously improve how we work through strong systems and small wins.
  • Build Leverage - We maximize impact with the right mix of people, tools, automation, and AI.
  • Crush the Challenge - We surface problems early and take ownership to solve them.
  • Go Fast - We take initiative, move with urgency, and bias toward action.
  • Be Creative - We challenge the norm and find better ways to win.
  • Lead with Empathy - We care deeply about our customers and each other.

If you thrive in fast-paced environments, take ownership of your work, and want to build something that actually moves the needle-join us and help shape what's next at True Classic!

Apply