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Insurance Risk Analyst Jobs in Michigan (NOW HIRING)

... analysis as needed as well as providing the client with accurate quotation for any additional ... S. brokerage firm offering comprehensive risk management advice, insurance and reinsurance ...

... analysis as needed as well as providing the client with accurate quotation for any additional ... S. brokerage firm offering comprehensive risk management advice, insurance and reinsurance ...

Sr Export Control Analyst

Farmington Hills, MI · On-site +1

$114K - $132K/yr

In your position, you will manage global risk, derive globally applicable governance requirements ... insurance; short- and long-term disability insurance; paid time off; parental leave, adoption ...

Performs a detailed analysis of a prospective client's needs by reviewing their existing insurance / risk management program; makes recommendations for appropriate and competitive coverages.

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Insurance Risk Analyst information

See Michigan salary details

$42.7K

$72.5K

$136K

How much do insurance risk analyst jobs pay per year?

As of Jul 9, 2026, the average yearly pay for insurance risk analyst in Michigan is $72,549.00, according to ZipRecruiter salary data. Most workers in this role earn between $56,700.00 and $75,400.00 per year, depending on experience, location, and employer.

How much does an insurance analyst make?

The average salary for an insurance risk analyst is around $70,000 to $85,000 per year, depending on experience, location, and certifications. Entry-level analysts typically earn less, while those with specialized skills or advanced credentials can earn higher salaries. Compensation may also include bonuses and benefits based on performance and company size.

What are some common challenges faced by Insurance Risk Analysts in evaluating emerging risks?

Insurance Risk Analysts often encounter challenges when assessing emerging risks such as cyber threats, climate change, or new technologies, as there may be limited historical data available. This requires them to continuously update their knowledge, collaborate with underwriters, actuaries, and external experts, and adopt advanced analytical tools to make informed recommendations. Staying proactive in identifying trends and adapting risk models is essential for success in this dynamic environment.

How much do risk analysts get paid?

Risk analysts in the insurance industry typically earn a median annual salary of around $70,000 to $90,000, depending on experience, location, and certifications. Entry-level positions may start lower, while experienced analysts with specialized skills can earn over $100,000 annually.

What are Insurance Risk Analysts?

Insurance Risk Analysts are professionals who assess and analyze potential risks that could affect an insurance company or its clients. They evaluate data and financial information to determine the likelihood and potential cost of events such as accidents, natural disasters, or other losses. Their work helps insurance companies set appropriate premiums and develop strategies to minimize financial loss. Insurance Risk Analysts also monitor trends and provide recommendations to reduce risk exposure.

What does a risk analyst do for an insurance company?

An insurance risk analyst evaluates potential risks that could affect an insurance company's financial stability by analyzing data, assessing risk exposure, and developing strategies to mitigate losses. They use statistical tools and industry knowledge to determine policy pricing and ensure the company's risk management aligns with regulatory standards.

What is the difference between Insurance Risk Analyst vs Insurance Underwriter?

AspectInsurance Risk AnalystInsurance Underwriter
Required CredentialsBachelor's degree in finance, economics, or related field; certifications like CPCU or ARM beneficialBachelor's degree in finance, economics, or related field; certifications like CPCU or ARM beneficial
Work EnvironmentAnalyzes data, assesses risks, and provides reports; often in an office settingEvaluates applications, determines policy terms, and approves or declines coverage; office-based
Employer & Industry UsageInsurance companies, risk management firms, consulting agenciesInsurance companies, brokerage firms, underwriting agencies

While both roles require similar credentials and work in the insurance industry, Insurance Risk Analysts focus on analyzing and quantifying risks to inform decision-making, whereas Insurance Underwriters evaluate individual applications to determine policy terms. Understanding these differences helps clarify career paths and employer expectations in the insurance sector.

What are the key skills and qualifications needed to thrive as an Insurance Risk Analyst, and why are they important?

To thrive as an Insurance Risk Analyst, you need strong analytical skills, a solid understanding of risk assessment methodologies, and typically a bachelor’s degree in finance, mathematics, or a related field. Familiarity with statistical software, risk modeling tools, and certifications such as Chartered Property Casualty Underwriter (CPCU) or Associate in Risk Management (ARM) are often required. Attention to detail, critical thinking, and effective communication are crucial soft skills for interpreting data and presenting findings to stakeholders. These skills ensure accurate risk evaluation, informed decision-making, and the development of effective risk mitigation strategies within insurance organizations.

Is risk analyst an entry level job?

A risk analyst position can be entry-level or require some experience, depending on the employer. Entry-level risk analyst roles typically require a bachelor's degree in finance, economics, or a related field, and may involve on-the-job training. Advanced roles may require additional certifications or experience in data analysis or risk management tools.

What Does an Insurance Risk Analyst Do?

An insurance risk analyst performs a variety of duties related to assessing risks your clients may undergo and how to insure them properly. You collect and analyze data, such as past claims in the industry, competitor pricing, and various risk management strategies to help your company keep costs down. Qualifications for the job include career training, education, and specialized skills. Typically, you need a bachelor’s degree in accounting or finance and some work experience in the industry. Important skills include an excellent eye for detail and strong analytical problem-solving.

What are popular job titles related to Insurance Risk Analyst jobs in Michigan? For Insurance Risk Analyst jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Insurance Risk Analyst jobs in Michigan look for? The top searched job categories for Insurance Risk Analyst jobs in Michigan are:
What are popular job titles related to Insurance Risk Analyst jobs in MI? For Insurance Risk Analyst jobs in MI, the most frequently searched job titles are:
Data Scientist Machine Learning Practitioner

Data Scientist Machine Learning Practitioner

BlueConduit

Ann Arbor, MI • On-site

$140K - $150K/yr

Full-time

Medical, Dental, Vision, Retirement

Posted 21 days ago


Job description

Company overview

BlueConduit is an infrastructure analytics SaaS company and social enterprise helping communities make better, faster, and more equitable decisions about critical water infrastructure. Our founding team pioneered predictive modeling for lead service line replacement in Flint, Michigan, and BlueConduit now works with hundreds of cities and utilities across North America.

Our platform helps utilities, municipalities, government agencies, and consultants combine fragmented infrastructure records, field observations, geospatial data, and predictive models to identify risk, prioritize work, meet compliance requirements, and communicate clearly with the public. We are a remote-first team committed to using data science for social good and building tools that are trusted by the people making high-stakes infrastructure decisions.

The role

BlueConduit is hiring a Data Scientist to improve and expand the machine learning models at the core of our infrastructure analytics platform. In this role, you will work on models that help cities prioritize infrastructure investments, reduce risk, and improve drinking water outcomes. You will strengthen our existing modeling workflows, help launch new model products and asset classes, and communicate results clearly to both technical and nontechnical audiences.

This is a strong fit for someone who combines rigorous applied ML judgment with product-minded execution: you enjoy messy real-world data, care about model validation and uncertainty, can build repeatable workflows rather than one-off analyses, and like explaining technical work to people who need to act on it.

In this role you will be expected to be using the latest available AI tools to code productively. You will need to understand what you're building and coding, and understand agentic AI workflows that involve best practices, including unit tests, built-in code reviews, and extensive documentation in your commits for fellow data scientists and software engineers.

This role reports to the VP of Data Science.

What you'll do
  • Build, validate, and improve machine learning and statistical models used in BlueConduit's infrastructure analytics products
  • Help design, build, and launch new model products and model classes that broaden the assets and risks BlueConduit can predict
  • Improve data science workflows, model evaluation, reproducibility, and handoffs into software/product systems
  • Work with heterogeneous municipal, infrastructure, geospatial, and field-observation datasets to generate actionable risk predictions
  • Design validation approaches and communicate model uncertainty, limitations, and tradeoffs clearly to internal teams and customers
  • Use modern AI coding tools such as Claude Code, Codex, or similar systems to accelerate development while applying strong independent programming judgment
  • Use multiple AI agents to contribute to extremely robust workflows and code pipelines with built-in testing and reviews
  • Support customer-facing analysis and present findings in ways that are clear, accurate, and useful for nontechnical decision-makers
  • Contribute to R&D that scales the impact, reliability, and reach of BlueConduit's predictive methods

BlueConduit is a small, remote, and growing team, so this is an opportunity to shape both the role and the next generation of our data science products.

What we're looking for
  • Strong Python-based data science experience, including pandas, NumPy, scikit-learn, and production-quality analysis workflows
  • An undergraduate degree in a quantitative field (e.g., CS, math, stats, physics)
  • Experience building, validating, and improving machine learning or statistical models on messy real-world data
  • Experience building repeatable data science workflows in a product at a SaaS company or similarly operational environment
  • Ability to communicate modeling results, uncertainty, and tradeoffs clearly to technical and nontechnical stakeholders
  • Fluency using modern AI coding tools including coordinating work of AI agents to accelerate development, grounded in strong independent programming ability and judgment
  • Strong data visualization, verbal communication, and written communication skills
  • Comfort with Git-based development workflows
  • Attention to detail, curiosity, and commitment to building models that are understandable, usable, and trusted by the people making infrastructure decisions
  • Passion for socially impactful data science, environmental justice, and public-interest technology
We're especially interested in candidates with one or more of the following
  • A rigorous graduate degree in a quantitative field, or equivalent applied experience
  • Experience modeling asset classes beyond BlueConduit's current water distribution portfolio, such as fire risk, wastewater, hydraulic systems, climate risk, insurance risk, or other infrastructure domains
  • Experience with geospatial data, GIS systems, GeoPandas, or spatial modeling
  • Experience creating a new model product or extending an existing model product to a new domain or asset class
  • Experience with both global/cross-location models and local/site-specific models
  • Experience with methodologies beyond classical ML, such as neural networks, transformers, transfer learning, or other modern ML approaches
  • Experience with cloud-based model workflows, model tracking, versioning, Databricks, PySpark, or distributed computing
  • Familiarity with infrastructure, water quality, government data, or regulated public-sector decision environments
  • Experience working in Agile product development environments
  • Aptitude and interest in building with rapid iteration cycles involving prototyping, receiving feedback, and rebuilding
Location

Remote

Compensation
  • Expected salary range: $140,000$150,000, commensurate with experience
  • Equity options
  • Health, vision and dental benefits
  • Simple IRA benefit with company contribution matching

Every qualified applicant will receive consideration for employment without regard to race, age, color, religion, sex, sexual orientation, or national origin.