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Senior Insurance Data Analytics Jobs in Missouri

TKC Holdings

Senior Data Analyst Engineer

Saint Louis, MO · On-site

$100K - $160K/yr

About This Position TKC Holdings is seeking a highly skilled Senior Data & Analytics Engineer to ... Basic Life and Basic Accidental Death and Dismemberment Insurance * Short Term Disability ...

TKC Holdings

Senior Data Analyst Engineer

Saint Louis, MO · On-site

$100K - $160K/yr

About This Position TKC Holdings is seeking a highly skilled Senior Data & Analytics Engineer to ... Basic Life and Basic Accidental Death and Dismemberment Insurance * Short Term Disability ...

Keefesupply

Senior Data Analyst Engineer

Saint Louis, MO · On-site

$100 - $160/hr

About This Position TKC Holdings is seeking a highly skilled Senior Data & Analytics Engineer to ... Basic Life and Basic Accidental Death and Dismemberment Insurance * Short Term Disability ...

New

Jobgether

$66K - $83K/yr

This is a senior analytics role focused on turning complex player and product data into insights that improve engagement, retention, monetization, and overall player experience. You will work closely ...

Walmart

(USA) Senior, Data Analyst

Anderson, MO · On-site

$80K - $155K/yr

Strong knowledge of relational databases, NoSQL, and big data analytics to support data integration ... Financial benefits include 401(k), stock purchase and company-paid life insurance. Paid time off ...

Walmart

(USA) Senior, Data Analyst

Noel, MO · On-site

$80K - $155K/yr

Strong knowledge of relational databases, NoSQL, and big data analytics to support data integration ... Financial benefits include 401(k), stock purchase and company-paid life insurance. Paid time off ...

Walmart

(USA) Senior, Data Analyst

Cassville, MO · On-site

$80K - $155K/yr

Strong knowledge of relational databases, NoSQL, and big data analytics to support data integration ... Financial benefits include 401(k), stock purchase and company-paid life insurance. Paid time off ...

Shelter Insurance

Business Data Specialist

Columbia, MO · On-site

$101K - $125K/yr

Proven experience (4+ years) as a Data Analyst or Insurance Business Analyst or a similar role, with a focus on analyzing complex data sets and providing actionable insights typically required.

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Senior Insurance Data Analytics information

What does a senior insurance data analytics professional do?

A Senior Insurance Data Analytics professional analyzes large datasets to help insurance companies make informed decisions about risk, pricing, claims, and customer behavior. They use statistical methods, data modeling, and business intelligence tools to uncover trends and insights that can improve operational efficiency and profitability. In addition to interpreting complex data, they often collaborate with other departments to develop data-driven strategies and may oversee or mentor junior analysts within the team.

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

To thrive as a Senior Insurance Data Analytics professional, you need a strong background in statistics, data analysis, and domain knowledge of insurance, often supported by a degree in mathematics, statistics, or a related field. Expertise in data analytics tools such as SQL, Python, R, and experience with business intelligence platforms like Tableau or Power BI are typically required. Strong problem-solving skills, attention to detail, and the ability to communicate complex insights clearly set top performers apart in this role. These skills are crucial for driving data-driven decision-making, identifying business opportunities, and improving risk assessment and operational efficiency within insurance organizations.

What are some common challenges faced by senior insurance data analytics professionals when working with large and complex datasets?

Senior Insurance Data Analytics professionals often encounter challenges such as integrating data from multiple legacy systems, ensuring data quality and accuracy, and managing sensitive information in compliance with regulations. Additionally, translating complex analytical findings into actionable insights for non-technical stakeholders can be demanding. Overcoming these challenges requires strong technical skills, clear communication, and close collaboration with IT, underwriting, and actuarial teams.

What is the difference between Senior Insurance Data Analytics vs Insurance Data Analyst?

AspectSenior Insurance Data AnalyticsInsurance Data Analyst
Required CredentialsBachelor's or Master's in Data Science, Statistics, or related field; often with experience in insurance analyticsBachelor's in related field; entry to mid-level experience
Work EnvironmentSenior roles often involve leadership, project management, and strategic planning within insurance companiesFocus on data collection, analysis, and reporting under supervision or team guidance
Employer & Industry UsageUsed across insurance firms, especially in analytics, underwriting, and actuarial departmentsCommonly employed in insurance companies, focusing on data processing and reporting

Senior Insurance Data Analytics professionals typically have more experience, advanced skills, and leadership responsibilities compared to Insurance Data Analysts. While both roles require strong analytical skills and familiarity with insurance data, seniors often oversee projects, develop strategies, and mentor junior staff, whereas analysts focus on data analysis and reporting tasks.

What are the most commonly searched types of Insurance Data Analytics jobs in Missouri?

The most popular types of Insurance Data Analytics jobs in Missouri are:

What cities in Missouri are hiring for Senior Insurance Data Analytics jobs?

Cities in Missouri with the most Senior Insurance Data Analytics job openings:

Senior Insurance Data Analytics jobs near you

Senior IT Manager - Data, Integration & Advanced Analytics

Jobtailor

California, MO • On-site

$180 - $240/hr

Other

Posted 2 days ago

New

Job description

Responsibilities
  • Define and execute enterprise strategies for Data, Integration, Analytics, and AI capabilities aligned with business objectives and enterprise architecture.
  • Develop and maintain multi-year roadmaps that advance data modernization, analytics transformation, AI adoption, and integration capabilities.
  • Identify strategic opportunities to improve business outcomes through data‑driven decision making and intelligent automation.
  • Partner with business and technology leaders to align investments with enterprise priorities and long‑term growth objectives.
  • Lead a portfolio of enterprise data, integration, analytics, and AI initiatives from concept through value realization.
  • Establish prioritization frameworks, governance processes, and delivery models that maximize business value.
  • Drive program execution, risk management, resource planning, and executive reporting across strategic initiatives.
  • Ensure initiatives are delivered successfully while meeting business objectives, quality standards, and financial targets.
  • Serve as a trusted advisor to senior business and technology leaders.
  • Translate business priorities into technology and analytics strategies that drive measurable outcomes.
  • Build strong partnerships across Commercial, Operations, Supply Chain, Finance, Quality, Manufacturing, and R&D organizations.
  • Communicate vision, strategy, progress, and business value to executive stakeholders.
  • Establish governance frameworks that ensure scalable, secure, compliant, and reusable enterprise solutions.
  • Drive adherence to enterprise architecture principles, data governance standards, privacy requirements, and regulatory expectations.
  • Promote consistency, standardization, and reuse across enterprise data and integration ecosystems.
  • Define and monitor key performance indicators that measure business value, adoption, solution quality, and delivery effectiveness.
  • Drive enterprise adoption of advanced analytics, AI, machine learning, and intelligent decision‑support capabilities.
  • Identify and prioritize high‑value opportunities that leverage analytics and AI to improve business performance.
  • Enable development of modern data products, semantic layers, self‑service analytics, and conversational intelligence solutions.
  • Foster innovation through emerging technologies and industry‑leading practices.
  • Lead and develop high‑performing global teams consisting of employees, contractors, and strategic partners.
  • Create a culture of accountability, innovation, collaboration, and continuous improvement.
  • Mentor leaders and team members to strengthen technical, business, and leadership capabilities.
  • Develop workforce strategies, succession plans, and talent pipelines to support future organizational needs.
  • Establish organizational goals and objectives aligned with broader business and technology strategies.
  • Champion inclusion, diversity, equity, and employee engagement across the organization.
  • Support portfolio planning, budgeting, investment prioritization, and financial management activities.
  • Partner with strategic vendors and technology providers to enable successful execution of business objectives.
  • Drive cost optimization and value realization across technology investments and initiatives.
Requirements
  • 7+ years of experience with a bachelor’s degree or 5+ years of experience with an advanced degree
  • 5+ years of managerial experience
  • Bachelor's or Advanced Degree in Computer Science, Information Technology, Data Analytics, Engineering, Business, or a related field.
  • 10+ years of experience in Data, Analytics, Integration, AI, or Digital Technology leadership roles.
  • 5+ years leading large global teams, managers, and complex strategic programs.
  • Experience delivering enterprise data platforms, integration ecosystems, analytics solutions, and AI initiatives.
  • Knowledge of modern cloud data, analytics, AI, and integration technologies.
  • Experience in MedTech, Healthcare, Life Sciences, or other regulated industries.
  • Strong track record of building strategic partnerships and influencing senior leaders.
  • Proven ability to drive business transformation through data and analytics.
  • Strong communication, organizational leadership, financial management, and stakeholder management skills.
  • For Baccalaureate degrees earned outside of the United States, a degree that satisfies the requirements of 8 C.F.R. § 214.2(h)(4)(iii)(A) is required.
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