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Overnight Insurance Data Analytics Jobs in Missouri

Candidates must have a strong analytics and data validation background. Key Responsibilities ... insurance, or operational data) * Experience with Databricks and/or PySpark Skills: Data Analyst ...

Mentor team members on analytics methods, data quality standards, and visualization best practices ... Financial benefits include 401(k), stock purchase and company-paid life insurance. Paid time off ...

(USA) Principal, Data Analyst

Noel, MO · On-site

$90K - $180K/yr

Mentor team members on analytics methods, data quality standards, and visualization best practices ... Financial benefits include 401(k), stock purchase and company-paid life insurance. Paid time off ...

Mentor team members on analytics methods, data quality standards, and visualization best practices ... Financial benefits include 401(k), stock purchase and company-paid life insurance. Paid time off ...

A minimum of 1-2 years' experience in the insurance industry, specifically in employee welfare benefits or pharmacy data analytics * Knowledge of the Pharmacy Benefit Management (PBM) industry ...

(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 ...

(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 ...

(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 ...

Data Analyst

California, MO · On-site

$82.92 - $89.25/hr

... advanced analytics (regression, clustering, time series, etc.). * Lead implementation of ... We offer a comprehensive benefits package that includes medical, dental, and vision insurance; paid ...

New

$66K - $83K/yr

Requirements * 2+ years of professional experience in data analytics or a related analytical field ... Health insurance with access to high-quality medical providers. * Coverage for psychological ...

Showing results 21-40

Overnight Insurance Data Analytics information

What is overnight insurance data analytics?

Overnight Insurance Data Analytics refers to the process of analyzing insurance data during overnight shifts or using automated systems to process large volumes of data outside of regular business hours. This ensures that insurance companies can quickly identify trends, detect fraud, and make informed decisions by the start of the next business day. Professionals in this role typically work with claims data, customer information, and risk assessments using advanced analytical tools and software. The goal is to improve operational efficiency and support decision-making processes.

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

To excel in Overnight Insurance Data Analytics, you need strong analytical abilities, proficiency in statistical methods, and a background in mathematics, statistics, or a related field. Familiarity with data analysis tools such as SQL, Python, R, and insurance-specific software is often required, along with experience in using data visualization platforms like Tableau or Power BI. Attention to detail, problem-solving skills, and the ability to communicate findings clearly are essential soft skills for this role. These competencies are vital for accurately interpreting large datasets during non-standard hours, supporting timely business decisions, and identifying trends or anomalies that impact insurance operations.

What unique challenges might I encounter working in an overnight insurance data analytics role?

Working overnight in insurance data analytics can present unique challenges, including adjusting to non-traditional work hours and maintaining effective communication with daytime teams. You may often handle urgent data requests or last-minute reporting, which requires strong problem-solving skills and the ability to work independently. Additionally, you’ll likely need to coordinate with colleagues across different time zones and shifts to ensure seamless handoffs and continuity in analytics projects. Adapting to the overnight schedule while maintaining high attention to detail and data integrity is essential for success in this role.

What is the difference between Overnight Insurance Data Analytics vs Underwriting Analyst?

AspectOvernight Insurance Data AnalyticsUnderwriting Analyst
CredentialsBachelor's in Data Science, Statistics, or related field; certifications like CAP, CPCU beneficialBachelor's in Business, Finance, or related field; certifications like CPCU or ARM advantageous
Work EnvironmentData centers, analytics teams, remote or office settingsInsurance companies, underwriting departments, office settings
Industry UsageFocuses on analyzing insurance data overnight to support decision-makingEvaluates risks and determines policy terms for insurance applications

While both roles involve insurance data, Overnight Insurance Data Analytics primarily focuses on analyzing data during overnight shifts to inform business decisions, whereas Underwriting Analysts assess risks and set policy terms. The roles share similar credentials but differ in daily tasks and work environment.

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 Overnight Insurance Data Analytics jobs?

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

Data & Analytics Engineer with Security Clearance

Gridiron IT Solutions

Saint Louis, MO • On-site

$70 - $80/hr

Contractor

Medical, Dental, Vision, Life, Retirement

Re-posted 15 days ago


Job description

Description: Gridiron IT is looking to hire a Data & Analytics Engineer to support a government program in St. Louis, MO. Role Overview: The Data and Analytics Engineer plays a crucial role in the implementation and ongoing support of the Network Operations Center (NOC) and Security Operations Center (SOC). This position is responsible for designing, implementing, and maintaining the data infrastructure and analytics capabilities that power both centers. The Data and Analytics Engineer works closely with NOC and SOC teams to ensure efficient data collection, processing, storage, and analysis, enabling data-driven decision-making and enhancing operational effectiveness. This Data and Analytics Engineer role is essential for building and maintaining the data infrastructure that powers modern NOC and SOC operations. The position requires a blend of technical expertise in data engineering, analytics, and an understanding of operational security and network management to deliver insights that drive effective decision-making and enhance overall operational capabilities. Key Responsibilities: - Design and implement scalable data architectures to support NOC and SOC operations - Develop data models that accommodate various data sources and types (e.g., logs, metrics, alerts) - Develop and maintain data pipelines to ingest data from various sources into NOC/SOC systems - Implement ETL (Extract, Transform, Load) processes for data normalization and enrichment - Ensure data quality and consistency across different systems and tools - Implement and manage big data technologies (e.g., Hadoop, Spark) to handle large volumes of NOC/SOC data - Optimize data storage and retrieval for efficient analysis and reporting - Design and implement real-time data processing and analytics capabilities - Develop streaming analytics solutions for immediate insights on network and security events - Create interactive dashboards and visualizations for NOC and SOC teams - Develop custom reports and analytics views for various stakeholders - Implement data governance policies and procedures for NOC/SOC data - Ensure data security and privacy compliance (e.g., data masking, access controls) - Develop and maintain data retention and archiving strategies Requirements: Bachelors degree
Years of Experience: 5-10 Skills:
Data Analysis. Data Analytic Tools - PowerBI, Advanced Excel. Clearance:
Applicants selected will be subject to a security investigation and may need to meet eligibility requirements for access to classified information. Compensation and Benefits: Salary Range: $70-80 hourly (Compensation is determined by various factors, including but not limited to location, work experience, skills, education, certifications, seniority, and business needs. This range may be modified in the future.) Benefits: Gridiron offers a comprehensive benefits package including medical, dental, vision insurance, HSA, FSA, 401(k), disability & ADD insurance, life and pet insurance to eligible employees. Full-time and part-time employees working at least 30 hours per week on a regular basis are eligible to participate in Gridiron’s benefits programs. Gridiron IT Solutions is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, gender identity, national origin, age, protected veteran status or disability status. Gridiron IT is a Women Owned Small Business (WOSB) headquartered in the Washington, D.C. area that supports our clients' missions throughout the United States. Gridiron IT specializes in providing comprehensive IT services tailored to meet the needs of federal agencies. Our capabilities include IT Infrastructure & Cloud Services, Cyber Security, Software Integration & Development, Data Solution & AI, and Enterprise Applications. These capabilities are backed by Gridiron IT's experienced workforce and our commitment to ensuring we meet and exceed our clients' expectations.