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Associate In Insurance Data Analytics Jobs in North Carolina

Barclays Bank Delaware seeks Data Analytics Lead, AVP in Wilmington, DE (multiple positions available): * Develop analytical strategy to achieve acquisitions marketing goals through the development ...

AI & Data Analytics Architect

Charlotte, NC

$62.25 - $80/hr

Demonstrated expertise in Azure data and analytics services. * Demonstrated experience with data security and privacy protection measures. * Proactively stay informed on new technologies and ...

Senior Data Architect

Charlotte, NC ยท On-site

$65.75 - $88/hr

... in Databricks and a strong understanding of the insurance industry. The ideal candidate will design and implement scalable data architectures that support advanced analytics, reporting, and AI/BI/ML ...

Senior Data Architect

Charlotte, NC

$65.75 - $88/hr

... in Databricks and a strong understanding of the insurance industry. The ideal candidate will design and implement scalable data architectures that support advanced analytics, reporting, and AI/BI/ML ...

Senior Enterprise Data Analyst

Raleigh, NC ยท On-site

$83K - $105K/yr

Builds dashboards to modernize analytics and assists management with special data projects ... Encourages discussion and feedback from associates in order to identify areas of improvement within ...

Senior Enterprise Data Analyst

Raleigh, NC ยท On-site

$83K - $105K/yr

Builds dashboards to modernize analytics and assists management with special data projects ... Encourages discussion and feedback from associates in order to identify areas of improvement within ...

You'll also lead a team in developing impactful data visualizations and dashboards, providing ... life insurance, parental benefits, adoption assistance, paid time off program with paid holidays ...

You'll also lead a team in developing impactful data visualizations and dashboards, providing ... life insurance, parental benefits, adoption assistance, paid time off program with paid holidays ...

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Associate In Insurance Data Analytics information

What are some common challenges faced by an Associate in Insurance Data Analytics, and how can they be addressed?

Associates in Insurance Data Analytics often encounter challenges such as working with large, complex datasets and ensuring data accuracy for reliable analysis. Additionally, interpreting data in the context of insurance policies and risk models requires both technical and industry-specific knowledge. Collaborating closely with underwriters, actuaries, and claims teams can help bridge knowledge gaps and enhance data-driven decision-making. Staying up-to-date with analytical tools and best practices can also help overcome these challenges and support career growth.

Is 40 too late for data science?

For an Associate in Insurance Data Analytics, age is not a barrier to entering data science. Many professionals successfully transition into data analytics roles later in their careers by acquiring relevant skills such as programming, statistics, and data visualization, often through online courses or certifications. Experience and continuous learning are valued more than age in this field.

How much does an insurance analyst make?

An insurance analyst typically earns between $55,000 and $85,000 annually, depending on experience, location, and the complexity of data analysis tasks. Entry-level roles may start lower, while experienced analysts with advanced skills in data tools like SQL or Python can earn higher salaries.

What is the difference between Associate In Insurance Data Analytics vs Insurance Data Analyst?

AspectAssociate In Insurance Data AnalyticsInsurance Data Analyst
Required CredentialsBachelor's degree in data science, statistics, or related field; certifications like CAP or CPCU beneficialBachelor's degree in data analysis, statistics, or related field; certifications like CAP or CPCU beneficial
Work EnvironmentEntry-level role in insurance companies or consulting firms, focusing on data collection and basic analysisMid-level role in insurance companies, analyzing data to support underwriting, claims, and risk assessment
Employer & Industry UsageCommonly used in insurance firms, agencies, and consulting firms for data support rolesUsed within insurance companies for data-driven decision making and reporting

The Associate In Insurance Data Analytics and Insurance Data Analyst roles share similar educational backgrounds and industry usage. However, the Associate role is typically entry-level, focusing on data collection and basic analysis, while the Insurance Data Analyst often has more experience and handles more complex data analysis tasks to support business decisions.

What are the key skills and qualifications needed to thrive as an Associate in Insurance Data Analytics, and why are they important?

To thrive as an Associate in Insurance Data Analytics, you need strong analytical skills, proficiency in statistics, and a background in insurance or finance, often supported by a relevant degree. Familiarity with data analysis tools like SQL, Python, R, and insurance-specific platforms or certifications such as the CPCU or AIDA is highly valued. Attention to detail, problem-solving abilities, and effective communication are critical soft skills for interpreting data and conveying insights to stakeholders. These skills are essential for transforming complex insurance data into actionable strategies that drive business decisions and risk management.

What are Associate In Insurance Data Analytics?

An Associate in Insurance Data Analytics is a professional who specializes in analyzing data within the insurance industry to help companies make informed decisions. They use statistical methods, data modeling, and business intelligence tools to derive insights about risk, customer behavior, and market trends. This role often requires knowledge of insurance processes, as well as technical skills in data analysis and interpretation. They play a key part in helping insurers optimize underwriting, pricing, claims, and customer experience.

What can you do with an associate's in data analytics?

An associate's in data analytics prepares individuals for roles such as data analyst or insurance data analyst, where they analyze data sets to identify trends and support decision-making. These roles often involve using tools like Excel, SQL, or data visualization software and may require understanding insurance industry data and basic statistical skills.

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 and support decision-making. They often use tools like Excel, SQL, and data visualization software to create reports and improve risk assessment, pricing, and fraud detection.
What are popular job titles related to Associate In Insurance Data Analytics jobs in North Carolina? For Associate In Insurance Data Analytics jobs in North Carolina, the most frequently searched job titles are:
What job categories do people searching Associate In Insurance Data Analytics jobs in North Carolina look for? The top searched job categories for Associate In Insurance Data Analytics jobs in North Carolina are:
What cities in North Carolina are hiring for Associate In Insurance Data Analytics jobs? Cities in North Carolina with the most Associate In Insurance Data Analytics job openings:
Infographic showing various Associate In Insurance Data Analytics job openings in North Carolina as of July 2026, with employment types broken down into 93% Full Time, and 7% Contract. Highlights an 86% In-person, and 14% Remote job distribution.
Data Analytics Lead, AVP

Data Analytics Lead, AVP

Barclays

Wilmington, NC โ€ข Hybrid

Full-time

Posted 21 days ago


Job description

hackajob is collaborating with Barclays to connect them with exceptional professionals for this role.

What will you be doing?

Barclays Bank Delaware seeks Data Analytics Lead, AVP in Wilmington, DE (multiple positions available):

  • Develop analytical strategy to achieve acquisitions marketing goals through the development of optimized product, offer and targeting.

  • Problem solve complex analytical/business issues to generate profitable new account growth while effectively managing risk.

  • Enhance analytical rigor for critical investment decisions and targeting leveraging advanced analytics, risk/reward segmentations & robust continuous testing.

  • Measure, monitor and benchmark all aspects of direct mail and email acquisitions performance against plan, actuals and competition.

  • Leverage cutting edge tools and techniques to optimize risk versus reward decisions around targeting and partner data.

  • Create continuous improvement cycle across channels to drive growth leveraging new data and segmentation techniques to drive speed to market through analytics

  • Work closely with Partnership, Risk, Finance, Marketing and other stakeholders across the bank.

  • Collaborate with key stakeholders to identify new opportunities and advise Senior Management on growth initiatives.

  • Provide business updates to leaders across the Partnership Business and key partners.

  • Optimize investment decisions across all critical components including offer, channel, product, targeting, CPA, pricing, and valuations.

  • May telecommute pursuant to company policies. [Hybrid role]

Purpose of the role

To extract meaningful insights from complex data sets, developing robust decision models, and presenting actionable recommendations to stakeholders across the departments. 

Accountabilities

  • Identification and extraction of relevant data from various internal and external sources.
  • Performing sensitivity analysis and scenario planning.
  • Monitoring and evaluation of the performance of existing models.
  • Development and implementation of data quality control procedures.
  • Building and validation of quantitative models to support decision-making across different business areas.

Assistant Vice President Expectations

  • To advise and influence decision making, contribute to policy development and take responsibility for operational effectiveness. Collaborate closely with other functions/ business divisions.
  • Lead a team performing complex tasks, using well developed professional knowledge and skills to deliver on work that impacts the whole business function. Set objectives and coach employees in pursuit of those objectives, appraisal of performance relative to objectives and determination of reward outcomes
  • If the position has leadership responsibilities, People Leaders are expected to demonstrate a clear set of leadership behaviours to create an environment for colleagues to thrive and deliver to a consistently excellent standard. The four LEAD behaviours are: L โ€“ Listen and be authentic, E โ€“ Energise and inspire, A โ€“ Align across the enterprise, D โ€“ Develop others.
  • OR for an individual contributor, they will lead collaborative assignments and guide team members through structured assignments, identify the need for the inclusion of other areas of specialisation to complete assignments. They will identify new directions for assignments and/ or projects, identifying a combination of cross functional methodologies or practices to meet required outcomes.
  • Consult on complex issues; providing advice to People Leaders to support the resolution of escalated issues.
  • Identify ways to mitigate risk and developing new policies/procedures in support of the control and governance agenda.
  • Take ownership for managing risk and strengthening controls in relation to the work done.
  • Perform work that is closely related to that of other areas, which requires understanding of how areas coordinate and contribute to the achievement of the objectives of the organisation sub-function.
  • Collaborate with other areas of work, for business aligned support areas to keep up to speed with business activity and the business strategy.
  • Engage in complex analysis of data from multiple sources of information, internal and external sources such as procedures and practises (in other areas, teams, companies, etc).to solve problems creatively and effectively.
  • Communicate complex information. 'Complex' information could include sensitive information or information that is difficult to communicate because of its content or its audience.
  • Influence or convince stakeholders to achieve outcomes.

All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence and Stewardship โ€“ our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset โ€“ to Empower, Challenge and Drive โ€“ the operating manual for how we behave.