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Overnight Insurance Data Analytics Jobs in Tennessee

... analyst tool/IDQ Knowledge of XML and other databases like DB2, teradata and SQL ... Experience in insurance data models Qualifications Excellent written and verbal communication ...

Senior Data Engineer

Memphis, TN · On-site

$103K - $140K/yr

... insurance data. Responsibilities : • Design and build data ingestion pipelines from multiple ... analytics reporting. • Maintain Feature Store pipelines that produce machine learning-ready ...

Senior Data Engineer

Memphis, TN · On-site

$95K - $129K/yr

... and insurance data into structured intelligence signals used for identification scoring, analytics, and operational reporting. The role requires deep experience with cloud data platforms, strong ...

Senior Data Engineer

Memphis, TN · On-site

$95K - $129K/yr

... and insurance data into structured intelligence signals used for identification scoring, analytics, and operational reporting. The role requires deep experience with cloud data platforms, strong ...

Senior Data Engineer

Memphis, TN

$95K - $129K/yr

... and insurance data into structured intelligence signals used for identification scoring, analytics, and operational reporting. The role requires deep experience with cloud data platforms, strong ...

Continuously develop knowledge of data analytics concepts, tools, technologies, and data sources ... With industry knowledge and expertise in accounting, tax, advisory, benefits, insurance, and ...

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Overnight Insurance Data Analytics information

What are 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 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 key skills and qualifications needed to thrive as an Overnight Insurance Data Analytics professional, and why are they important?

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.

Is 40 too late for data science?

For an Overnight Insurance Data Analytics role, age is not a barrier; many professionals transition into data science or analytics later in their careers. Success depends on skills, experience, and continuous learning, such as mastering tools like SQL, Python, or R, and gaining relevant certifications. Age should not deter pursuing a data analytics career at 40 or older.

Will AI replace a data analyst?

AI can automate routine data processing and basic analysis tasks, but the role of a data analyst, including an Overnight Insurance Data Analytics professional, involves interpreting complex data, providing insights, and making strategic decisions that require human judgment. AI tools are used to enhance efficiency, but they do not fully replace the need for skilled analysts who understand business context and can communicate findings effectively.

Can a data analyst work at night?

A data analyst, including those working in insurance data analytics, can work night shifts if the employer offers overnight or flexible schedules. Some roles require 24/7 coverage or support for global operations, making night work possible, especially in environments with real-time data monitoring or client support. Skills in remote collaboration tools and time management are helpful for night shift work.

What does a data analyst do in insurance?

A data analyst in insurance collects, processes, and analyzes data related to policies, claims, and customer information to identify trends, assess risks, and support decision-making. They often use tools like Excel, SQL, and data visualization software to create reports and insights that help improve underwriting, pricing, and fraud detection.
What are the most commonly searched types of Insurance Data Analytics jobs in Tennessee? The most popular types of Insurance Data Analytics jobs in Tennessee are:
What cities in Tennessee are hiring for Overnight Insurance Data Analytics jobs? Cities in Tennessee with the most Overnight Insurance Data Analytics job openings:
Data Analyst

Full-time

Posted 12 days ago


Job description

Company Description

Tech Tammina LLC

Job Description

Experience Required: 6+ years

Strong experience in source to target mapping, and metadata management.   

Strong SQL knowledge with complex queries including joins etc. 

Excellent skills in logical and physical data modeling and normalization of data. 

knowledge with Informatica data analyst tool/IDQ 

Knowledge of XML and other databases like DB2, teradata and SQL. 

Experience in insurance data models

Qualifications

Excellent written and verbal communication skills to keep executive staff and team members apprised of goals, project status, and resolve issues and conflicts. 

Ability to quickly learn new concepts and software is necessary

Additional Information

Job Status: Full Time 

Eligiblity: GC or US Citizens

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Contact: 703-349-1214

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