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Associate In Insurance Data Analytics Jobs in Virginia

Senior Consultant - Data & Analytics

Mclean, VA · On-site

$86K - $109K/yr

Our consultants are hands-on problem solvers who partner closely with clients in fast-paced, project-based environments. Your Impact As a Senior Consultant, Data & Analytics, you will: * Design and ...

This role is located at a client site in either Reston, VA. A hybrid working model is acceptable ... Comprehensive insurance options . Matching contributions through the 401(k) plan and the share ...

New

This position is located in our Arlington, VA office; however, a hybrid working model is acceptable ... insurance options • Matching contributions through the 401(k) plan and the share purchase plan ...

$48K - $115K/yr

The Data & Analytics Senior Analyst works at the direction of a Team Leader to fulfill the data and ... Delivers analytical solutions, in a timely and accurate manner, with some direction from their ...

Senior Data Analyst

Quantico, VA · On-site

$91K - $114K/yr

Minimum 10 years of professional experience in data science or advanced analytics * Experience with ... Microsoft Technical Associate (MTA), MCPD, MCSD, MCSE * Certificate of Cloud Security Knowledge ...

The ideal candidate has demonstrated experience leading enterprise data initiatives in regulated ... Lead enterprise data, analytics, governance, and AI-enabled capability delivery across a complex ...

Senior Data Analyst

Quantico, VA · On-site

$91K - $114K/yr

Minimum 10 years of professional experience in data science or advanced analytics * Experience with ... Microsoft Technical Associate (MTA), MCPD, MCSD, MCSE * Certificate of Cloud Security Knowledge ...

Our consultants are hands-on problem solvers who partner closely with clients in fast-paced, project-based environments. Your Impact As a Senior Consultant, Data & Analytics, you will: * Design and ...

Key Functions: • The candidate will be able to design and implement solutions for data/information integration, discovery, analysis, and visualization in large-scale data driven environments • ...

New

Proficiency in SQL: Essential for querying and managing data in relational databases, including ... Associate Google Data Analytics Professional Certificate Certified Analytics Professional (CAP) AWS ...

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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 Virginia? For Associate In Insurance Data Analytics jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Associate In Insurance Data Analytics jobs in Virginia look for? The top searched job categories for Associate In Insurance Data Analytics jobs in Virginia are:
What cities in Virginia are hiring for Associate In Insurance Data Analytics jobs? Cities in Virginia with the most Associate In Insurance Data Analytics job openings:

Full-time

Posted 5 hours ago


Job description

Job Summary:
Highspring is a consulting firm that focuses on delivering data and analytics solutions to Fortune 100 brands and mid-market firms. The Manager, Data & Analytics will lead projects to design and build data warehouses, develop data pipelines, and implement analytics solutions, while collaborating with clients to address their data challenges and business objectives.
Responsibilities:
• Design and build modern data warehouses and analytics-ready data models.
• Develop scalable, reliable data pipelines using cloud-based data platforms.
• Implement analytics, reporting, and visualization solutions that translate complex data into clear, actionable insights for client stakeholders.
• Partner with client teams to understand business objectives, data challenges, and success metrics through interviews and working sessions.
• Manage discrete project workstreams, balancing technical execution with client communication and delivery timelines.
• Present findings, recommendations, and solution designs to both technical and non-technical audiences.
• Leverage AI-assisted development environments to design, generate, test, and iterate on production-quality analytics and data engineering code.
• Support broader data transformation initiatives, including system implementations, migrations, and modernization efforts.
• Actively participate in internal knowledge sharing, mentoring, and career development activities.
• Support the shaping of the strategic direction of our growing AI/ML, automation, and Data Analytics practice.
• Deliver on projects in the areas of data management, data governance, dashboard monitoring, DQ dashboards, data controls, data lineage, and data mapping.
• Support data transformation initiatives across a range of service lines, including: M&A Lifecycle (integrations, divestitures, and carveouts), Finance Transformation, Enterprise Data Strategy / Governance Standup, Process Improvement and Automation, System Implementations / Migrations, Data and Automation Strategy and Road mapping (including how companies can leverage AI, ML, and other advanced data modeling concepts).
• Identify insights through use of statistical, algorithmic, mining and visualization techniques.
• Conduct interviews with client stakeholders to identify process and data challenges.
• Document and present findings to both technical and non-technical audiences.
• Develop analytical proof-of-concept prototypes and/ or deliver large-scale analytical platform implementations to fulfill clients’ tactical and strategic requirements.
• Develop business procedures and data management policies for ensuring data accuracy and control.
• Create model documentation, develop implementation roadmaps, and perform knowledge transfers.
Qualifications:
Required:
• 4+ years of data analytics, AI, ML, or GenAI experience
• Tier 1/Tier 2 consulting or professional services firms.
• Experience architecting and developing AI/ML solutions.
• Experience programming in Python, SQL, and/or R.
• Experience using GitHub (e.g., source code management).
• Comprehensive knowledge of modern statistical learning methods.
• Experience using applied statistics or machine learning in a professional or other intensive problem-solving environment with large, complex datasets.
• Experience with any of the following commercial analytics, automation, and AI/ML tools: Alteryx, Power BI, Tableau, Power Automate, UiPath, Automation Anywhere, AI/ML/GenAI platforms, Informatica, Oracle EDMC, etc.
• Proven ability to lead, motivate and build teams that deliver services and solutions that surpass client expectations.
• Ability to lead workshops, including the gathering/documenting of requirements and use-cases and recommendation of envisioned processes.
• Experience presenting to CXO suite.
• Industry experience within Financial Services, Technology/SaaS, and/or Supply Chain.
• Understanding of typical software development lifecycles (Waterfall and Agile) and their associated lifecycle artifacts.
• Experience with identifying and correcting problems in imperfect data and processes.
• Bachelor's degree in Mathematics, Statistics, Computer Science, Information Systems, or other technology-related field or equivalent number of years of experience
• Flexibility to accommodate travel up to 25%.
Preferred:
• Strong business skills and experience in accounting, corporate finance, and FP&A.
• Familiarity with the M&A transaction lifecycle.
• Master’s degree in Information Technology, Statistics, Physics, Analytics or related field.
• Experience managing technical development by acting as a liaison between the technical team and the user community.
Company:
MorganFranklin Consulting is now Highspring, a leading global professional services organization with three integrated offerings—Consulting, Managed Services, and Talent Solutions. Founded in 1998, the company is headquartered in Mclean, USA, with a team of 501-1000 employees. The company is currently Late Stage.