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Associate In Insurance Data Analytics Jobs in Idaho

Scentsy Inc

Data Engineer

Meridian, ID

$108K - $129K/yr

Participate in the design and build of conceptual, logical, and physical data models to support business analytics from the data warehouse * Recommend data strategies, ETL processes, and procedures ...

Scentsy Inc

Data Engineer

Meridian, ID

$108K - $129K/yr

Participate in the design and build of conceptual, logical, and physical data models to support business analytics from the data warehouse * Recommend data strategies, ETL processes, and procedures ...

Scentsy

Data Engineer

Meridian, ID · On-site

$108K - $129K/yr

Participate in the design and build of conceptual, logical, and physical data models to support business analytics from the data warehouse * Recommend data strategies, ETL processes, and procedures ...

Clearwater Analytics

Client Servicing Associate

Boise, ID · On-site

$54K - $70K/yr

These analysts play a pivotal role in delivering prompt, precise, and comprehensive responses to ... Validate investment data against available third-party market data sources and show proficiency in ...

Clearwater Analytics

Client Servicing Associate

Boise, ID · On-site

$54K - $70K/yr

These analysts play a pivotal role in delivering prompt, precise, and comprehensive responses to ... Validate investment data against available third-party market data sources and show proficiency in ...

Melaleuca

Associate Financial Analyst

Idaho Falls, ID

The Associate Financial Analyst position plays an integral part in the analysis, recommendation and ... Bachelor's Degree in Finance, Accounting, Economics, Strategy or Data Analytics * Strong academic ...

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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.
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What cities in Idaho are hiring for Associate In Insurance Data Analytics jobs? Cities in Idaho with the most Associate In Insurance Data Analytics job openings:
Associate In Insurance Data Analytics jobs near you
Data Engineer

Data Engineer

Scentsy Inc

Meridian, ID

$108K - $129K/yr

Other

Posted 28 days ago

Job description

Description

Scentsy is looking for a Data Engineer to ensure the availability, reliability, and performance of data infrastructure and analytical systems. This role pairs deep data engineering expertise with strong development capabilities, designing and building data products on AWS, S3, and other cloud data warehouse technologies.


This job is worked 100% of the time in-office at our Meridian, ID corporate office.

*Please note: We are unable to provide H-1B visa work sponsorship for this position.


What You'll Do:

  • Serve as part of our Data Engineering and Analytics team providing data analytics capabilities for various internal Scentsy business partners
  • Influence and evangelize analytical methodologies to support business partners' needs
  • Act as a technical lead for designing and implementing custom reports and dashboards 
  • Assess requirements and assist with developing data warehouse infrastructure 
  • Confer with the immediate team on warehouse operational issues and recommend resolutions
  • Interface with data analysts to define and implement data requirements to meet their analytic needs 
  • Participate in the design and build of conceptual, logical, and physical data models to support business analytics from the data warehouse
  • Recommend data strategies, ETL processes, and procedures for getting data in and out of the data warehouse 
  • Design, develop, and deploy data pipelines, integrations, and automation solutions, applying sound software engineering practices across the development lifecycle
  • Test reporting solutions and provide training
  • Interact with technical resources from various teams within the Information Systems and Information Technology departments to define and test technical changes to the system
  • Design and implement custom reports and dashboards
  • Translate analytical program models, including but not limited to scripting, error handling, and documentation 
  • Work with users from various functional areas (sales, order processing, shipping, logistics, credit, finance, marketing, etc.)
  • Analyze processes ensuring sustainability, supportability, and automation
  • Identify new data from additional internal or 3rd party systems and transform it to work cohesively within existing Data Warehousing models
  • Participate in evaluating new technologies to ensure data and technology architecture advancement within the organization's BI needs
  • Identify development needs to improve and streamline business operations
  • Provide stakeholders with quality data so the business can make sound, data-driven decisions and recommendations
  • Coach and mentor less experienced engineers
  • Perform all other assigned tasks and requirements as needed

We're Looking For:

  • Bachelor's degree in business, Business Intelligence, Data Warehouse or data related field or equivalent related experience
  • 5 years of data warehouse engineering experience and/or 3 years of Business Intelligence experience
  • Significant knowledge of best practices for data modeling, dimensional modeling (Star schema), data ingestion, queries, and data loading options
  • Wide experience of cloud data warehousing tools and technologies such as Snowflake and RedShift
  • Significant experience with BI tools such as AWS QuickSight, Power BI, R, Python, SAP Business Objects and Web Intelligence (WEBI) reporting tools
  • Experience with AWS Services like AWS Quick, Cloud Formation, S3, Glue, State Machine, Lambda, Event Bridge, SNS and Appflow.
  • Excellent data manipulation and analysis skills
  • Experience in data access and delivery technologies, including familiarity with data quality assessment, data organization, metadata, and data profiling
  • Ability to take complex, ambiguous problems, break them down into smaller parts, and problem solve to come up with a whole, integrated, and strategic solution
  • Excellent skills in SQL, data modeling, data warehousing, and OLAP
  • Strong solution development capabilities, including the ability to design, build, test, and deploy production-quality code and automation
  • Excellent written and oral communication skills
  • Experience with SAP systems including table structure, field definitions, CDS views and usage, a plus
  • Experience with git
  • Advanced critical thinking, problem solving, and analytical skills
  • Familiarity with Agile Framework
  • Experience with Redgate Flyway



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