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Overnight Insurance Data Analytics Jobs in Silver Spring, MD

Calibre CPA Group

Data Analyst

Bethesda, MD · On-site

$80K - $95K/yr

Occasional local or overnight travel as needed. REQUIRED EDUCATION AND EXPERIENCE * Bachelor's degree in Data Analytics, Accounting, Finance, Information Systems, Statistics, or a related field * Two ...

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Maximus

Senior Engineer - Data Analytics

VA · On-site +1

$106K - $144K/yr

Primarily engaged in building and supporting data, analytics, and business intelligence ... Additionally, Maximus provides a variety of benefits to employees, including health insurance ...

Insilico Logix

Data Analyst

Herndon, VA

$60K - $70K/yr

... Insurance - Immigration Support for OPT students and visa holders - Skills Enhancement Data Analytics Training Program is provided for selected candidates ** OPT students may also apply If you are ...

Guidehouse

FM Data Analysis Specialist

Mclean, VA · On-site

ONE (1) year+ experience in financial management and data analytics What Would Be Nice To Have ... Medical, Rx, Dental & Vision Insurance * Personal and Family Sick Time & Company Paid Holidays

Guidehouse

FM Data Analysis Specialist

Mclean, VA

ONE (1) year+ experience in financial management and data analytics What Would Be Nice To Have ... Medical, Rx, Dental & Vision Insurance * Personal and Family Sick Time & Company Paid Holidays

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All JobsInsurance Data Analytics JobsOvernight Insurance Data Analytics JobsOvernight Insurance Data Analytics Jobs in Silver Spring, MD

Overnight Insurance Data Analytics information

See Silver Spring, MD salary details

$158.2K

$184.8K

$208.8K

How much do overnight insurance data analytics jobs pay per year?

As of Jul 14, 2026, the average yearly pay for overnight insurance data analytics in Silver Spring, MD is $184,787.00, according to ZipRecruiter salary data. Most workers in this role earn between $171,100.00 and $198,000.00 per year, depending on experience, location, and employer.

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 cities near Silver Spring, MD are hiring for Overnight Insurance Data Analytics jobs? Cities near Silver Spring, MD with the most Overnight Insurance Data Analytics job openings:
Overnight Insurance Data Analytics jobs near you
Data Analyst

Data Analyst

Calibre CPA Group

Bethesda, MD • On-site

$80K - $95K/yr

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

POSITION SUMMARY
The Data Analyst supports engagement teams across the Firm with data manipulation, extraction, and reporting. This role also drives internal data analysis for firm operations and analyzes industry-relevant datasets (Form 5500s, LM-2s, and similar filings) to generate insights that support client service, business development, and firm strategy. The analyst is responsible for turning large or complex datasets into clean, accurate, and user-friendly outputs that non-technical stakeholders can act on.
Salary Range: $80,000 - $95,000 (depending on experience)
KEY RESPONSIBILITIES
Engagement Team Support
  • Assist engagement teams across service lines with data extraction and manipulation tasks including cleansing, reformatting, reconciling, and merging client-provided data files (GL detail, payroll registers, membership rosters, contribution files, AP/AR data, tax data, and other client datasets).
  • Build repeatable data workflows to streamline recurring engagement tasks such as sampling, testing, trend analysis, and reconciliations.
  • Create dashboards and reports that give engagement teams and clients quick visibility into key metrics and trends.
  • Run data analytics to identify miscoded transactions, outliers, duplicates, and other anomalies that warrant follow-up.

Internal Data Analysis
  • Analyze firm operational data including realization, utilization, WIP, billing, collections, staffing, and engagement profitability.
  • Support partners and firm leadership with ad hoc analytics for management committee reporting, engagement profitability, and resource planning.
  • Assist with data extraction and reporting from firm systems.

Industry and External Data Analysis
  • Extract, clean, and analyze publicly available data relevant to Calibre's client base, including Form 5500 filings, LM-2 filings, and other regulatory datasets.
  • Identify trends across labor unions, employee benefit plans, nonprofits, and commercial clients to support business development, proposals, and thought leadership.
  • Build benchmarking tools and comparative analyses that partners can use in client meetings and prospect conversations.

Presentation and Delivery
  • Present findings in clear, user-friendly formats including Excel workbooks, Power BI dashboards, and summary memos tailored to the audience.
  • Ensure outputs are accurate, well-documented, and easy for non-technical users to interpret and reuse.
  • Collaborate with IT and firm operations on data governance, source documentation, and version control.

COMPETENCIES
  • Strong analytical and problem-solving skills
  • Excellent oral and written communication skills, with the ability to translate technical findings for non-technical audiences
  • Attention to detail and commitment to accuracy
  • Ability to manage multiple projects and priorities across service lines
  • Discretion in handling confidential client and firm data
  • Collaborative and service-oriented mindset

POSITION TYPE
This is a full-time permanent position.
WORK ENVIRONMENT
Professional office environment with hybrid flexibility. Occasional travel to other Calibre offices or client sites may be required. Standard office equipment including computers, dual monitors, and collaboration tools.
TRAVEL
Minimal. Occasional local or overnight travel as needed.
REQUIRED EDUCATION AND EXPERIENCE
  • Bachelor's degree in Data Analytics, Accounting, Finance, Information Systems, Statistics, or a related field
  • Two or more years of experience in a data analyst or similar role
  • Proficiency in Excel (advanced formulas, Power Query, pivot tables) and SQL
  • Experience with data visualization tools such as Power BI or Tableau

PREFERRED EDUCATION AND EXPERIENCE
  • Experience working in or with a public accounting firm, professional services firm, or regulated industry
  • Familiarity with accounting systems (e.g., QuickBooks, Sage Intacct, NetSuite) or audit and tax workflows
  • Experience working with public regulatory datasets such as Form 5500, LM-2, or Census data
  • Exposure to Python, R, Alteryx, or other data manipulation platforms
  • Familiarity with AI-enabled analytics tools

WORK AUTHORIZATION
Must have valid work authorization for employment in the United States.
OTHER DUTIES
This job description is not designed to cover or contain a comprehensive listing of activities, duties, or responsibilities that are required of the employee for this job. Duties, responsibilities, and activities may change at any time with or without notice.

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