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Overnight Insurance Data Analytics Jobs in Arizona

Manager, Data Analytics

Tempe, AZ · Hybrid

$111K - $145K/yr

Oscar is the first health insurance company built around a full stack technology platform and a ... The Data Analytics Manager works across and outside the organization to solve complex data issues.

Manager, Data Analytics

Tempe, AZ · Hybrid

$111K - $145K/yr

Oscar is the first health insurance company built around a full stack technology platform and a ... The Data Analytics Manager works across and outside the organization to solve complex data issues.

Manager, Data Analytics

Tempe, AZ · On-site

$111K - $145K/yr

Oscar is the first health insurance company built around a full stack technology platform and a ... The Data Analytics Manager works across and outside the organization to solve complex data issues.

Pharmacist - Data Analytics

Chandler, AZ · On-site

$56.50 - $68/hr

You must have data analytics experience for this position. * PharmD preferred. * Experience working ... insurance, wellness programs and financial education resources, to name a few. Elevance Health ...

Factory Data Analytics Engineer

Tucson, AZ

$108K - $130K/yr

Create and maintain data visualization and statistical analysis tools that increase understanding ... life insurance, short-term disability, long-term disability, 401(k) match, flexible spending ...

Data Analyst

Phoenix, AZ · On-site

$90K - $130K/yr

This role provides opportunities to deepen your expertise in data analytics, data management, data ... Insurance Options: Auto & Home Insurance, Identity Theft Protection. Convenience & Professional ...

... insurance, 401K retirement savings plan, Life Insurance, Disability Insurance. Tasks and ... Performs data analytics on various processes and projects to measure post-implementation ...

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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 Arizona? The most popular types of Insurance Data Analytics jobs in Arizona are:
What cities in Arizona are hiring for Overnight Insurance Data Analytics jobs? Cities in Arizona with the most Overnight Insurance Data Analytics job openings:
Manager, Data Analytics

Manager, Data Analytics

Oscar Health

Tempe, AZ • Hybrid

$111K - $145K/yr

Other

PTO

Posted 29 days ago


Oscar Health rating

6.9

Company rating: 6.9 out of 10

Based on 6 frontline employees who took The Breakroom Quiz

247th of 298 rated insurance


Job description

Hi, we're Oscar. We're hiring a Data Analytics Manager to join our Operations Team.

Oscar is the first health insurance company built around a full stack technology platform and a relentless focus on serving our members. We started Oscar in 2012 to create the kind of health insurance company we would want for ourselves-one that behaves like a doctor in the family.

About the role:

The Data Analytics Manager works across and outside the organization to solve complex data issues. You will work collaboratively to assess data related issues, understand the cause of those issues, and partner with the engineering, data, and customer success teams to implement solutions. You will understand the use, flow, and generation of data within a complex ecosystem of business processes and will need to explain your findings to audiences with varying degrees of technical knowledge. You will drive the scoping & execution of analytical requests, including working with team members to define important questions, scope methodologies, and achieve results.

Work Location: This position is based in our Tempe, AZ office, requiring a hybrid work schedule with 3 days of in-office work per week. Thursdays are a required in-office day for team meetings and events, while your other two office days are flexible to suit your schedule. #LI-Hybrid

Pay Transparency: The base pay for this role is: $111,034.80 - $145,733.18 per year. You are also eligible for employee benefits, unlimited PTO and annual performance bonuses.

Responsibilities:

  • Communicate with external customers and our teams to evaluate data issues, serving as the first point of contract for production issues
  • Ask questions to determine the cause and business impacts of issues that are raised surrounding our data
  • Partner with engineering and data teams to find solutions to data issues within a complex system architecture that prioritize accuracy, customer satisfaction, and scalability
  • Partner with business teams to explain complex technical and data issues to non-technical colleagues, including packaging and presenting findings
  • Recognize the need to enhance essential operational and analytical dashboards, and define the requirements to enhance them as our users' needs evolve
  • Identify opportunities to create models and tools that improve processes and overall improve efficiency
  • Collaborate across the organization with internal and external leaders, to identify actions to achieve improvements and monitor initiative impact
  • Support other projects as assigned to meet our needs
  • Lead a team of data analysts
  • Compliance with all applicable laws and regulations (DO NOT REMOVE - REQUIRED)
  • Other duties as assigned (DO NOT REMOVE - REQUIRED)

Requirements:

  • 4+ years of technical work experience using analytical tools and writing analytical reports
  • 4+ years in a client-facing role with experience managing issues externally
  • 2+ years demonstrated ability to work with large datasets and distill analyses into relevant insights with a structured and systematic thought process
  • 5+ examples/projects of experience communicating updates and resolutions to customers and other partners, around business reporting impact and requirements
  • 2+ years experience in SQL, with the ability to filter, aggregate, and build CTEs, or proficiency in R or Python, including experience with Pandas, for loops, and statistical tests
  • 1+ years experience, including proficiency in Google Sheets or Excel skills, with ability to use VLookup, nested if statements and connected Sheets
  • 1+ years experience in healthcare, finance or the insurance industry

Bonus points:

  • 2+ years experience in preparing healthcare analytics, reporting, and data management
  • Experience with ticketing system (such as Jira)
  • Proficiency in R or Python, including experience with Pandas, for loops, and statistical tests

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