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Analytics Assistant Jobs in Raleigh, NC (NOW HIRING)

Technical Architect - Data, Analytics & AI

Durham, NC ยท Hybrid

$61.50 - $79.25/hr

Key Responsibilities * Assist in the development of a multiyear Data, Analytics, and AI roadmap , aligned with the Munich Re Target Architecture and Roadmap Development Process, in collaboration with ...

Technical Architect - Data, Analytics & AI

Cary, NC ยท Hybrid

$59 - $76/hr

Key Responsibilities * Assist in the development of a multiyear Data, Analytics, and AI roadmap , aligned with the Munich Re Target Architecture and Roadmap Development Process, in collaboration with ...

Accounts Payable Associate

Henderson, NC ยท On-site

$18.75 - $24/hr

Support audits by providing requested documentation and analysis. * Assist with the onboarding of new vendors, including W-9 collection and vendor setup. Qualifications: * High school diploma or ...

Accounts Payable Associate

Henderson, NC ยท On-site

$18.75 - $24/hr

Support audits by providing requested documentation and analysis. * Assist with the onboarding of new vendors, including W-9 collection and vendor setup. Qualifications: * High school diploma or ...

Associate Fulfillment Specialist

Raleigh, NC ยท On-site

$16 - $21.25/hr

Reporting and Analysis: * Assist in creating and maintaining basic reports and dashboards to track key order metrics. * Learn to analyze order data to identify trends, opportunities, and areas for ...

Associate Fulfillment Specialist

Raleigh, NC ยท On-site

$16 - $21.25/hr

Reporting and Analysis: * Assist in creating and maintaining basic reports and dashboards to track key order metrics. * Learn to analyze order data to identify trends, opportunities, and areas for ...

Student Research Assistant (CYSLE)

Raleigh, NC ยท On-site

$18.75 - $25.75/hr

Students are expected to assist faculty in the identification and dissemination of academic ... Students must participate in training of the statistical and thematic analysis of data. Students ...

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Analytics Assistant information

What are Analytics Assistants?

Analytics Assistants are professionals who support data analysis tasks within a company or organization. They help collect, organize, and process data, create reports, and assist senior analysts in interpreting information to guide business decisions. Their responsibilities often include using data management tools, preparing presentations, and ensuring data accuracy. Analytics Assistants play a vital role in transforming raw data into actionable insights. This entry-level position is ideal for those looking to start a career in data analytics.

What are the typical daily responsibilities of an Analytics Assistant and how do they contribute to team projects?

As an Analytics Assistant, your day-to-day tasks often include gathering and cleaning data, creating basic reports, and supporting more senior analysts with research and data visualization. You play a key role in ensuring data accuracy and timely delivery of insights, which helps the team make informed decisions. Collaboration with team members, such as analysts and project managers, is common, especially when preparing presentations or addressing urgent data requests. This role provides a strong foundation in analytics tools and processes, making it ideal for those aiming to advance in data-driven careers.

What does an assistant analyst do?

An assistant analyst supports data analysis tasks by collecting, organizing, and preparing data for review. They often use tools like Excel or statistical software, assist in generating reports, and help interpret data insights under the supervision of senior analysts.

What jobs make $1,000,000 a year?

In the field of analytics, high-paying roles such as Chief Data Officer, Data Science Director, or senior executive positions in large corporations can reach or exceed $1,000,000 annually, especially with bonuses and stock options. These roles typically require extensive experience, advanced skills in data management and analytics tools, and often involve leadership responsibilities. Most roles at this level are found in large organizations or consulting firms with significant revenue and data assets.

What is the difference between Analytics Assistant vs Data Analyst?

AspectAnalytics AssistantData Analyst
Required CredentialsAssociate's degree or relevant certificationsBachelor's degree in data-related fields, often with certifications
Work EnvironmentSupportive, entry-level roles in offices or remote settingsAnalytical, project-focused roles in various industries
Employer & Industry UsageCommon in marketing, finance, and tech companiesWidely used across industries for data-driven decision making
Search & Comparison IntentUnderstanding entry-level data support rolesAnalyzing differences in data-related job responsibilities

The main difference between an Analytics Assistant and a Data Analyst lies in their experience level, responsibilities, and qualifications. Analytics Assistants typically support data teams with basic tasks and require less advanced education, while Data Analysts handle more complex analysis and decision-making processes. Both roles are essential in data-driven organizations, but they differ in scope and expertise.

Can I be a data analyst with no experience?

Yes, entry-level data analyst positions often do not require prior experience if candidates have relevant skills such as proficiency in Excel, SQL, or data visualization tools, and a strong understanding of basic statistical concepts. Gaining certifications or completing online courses can also improve your chances of starting in this role.

What are the key skills and qualifications needed to thrive as an Analytics Assistant, and why are they important?

To thrive as an Analytics Assistant, you need a solid understanding of data analysis, statistics, and proficiency with spreadsheet and database tools, often supported by a degree in mathematics, statistics, or a related field. Familiarity with data visualization software (like Tableau or Power BI), SQL, and Microsoft Excel are typically required, and knowledge of programming languages like Python or R is beneficial. Attention to detail, analytical thinking, and strong communication skills help you interpret data accurately and convey insights effectively to stakeholders. These abilities are crucial for supporting data-driven decision-making and ensuring the accuracy and clarity of analytical reports.

Is 40 too late for data science?

For an Analytics Assistant or similar data-related roles, starting a career in data science at age 40 is possible. Many professionals transition into data science later in life by acquiring relevant skills such as programming, statistics, and tools like Python or R, often through online courses or certifications. Age is less important than skills, experience, and continuous learning in the field.
What are the most commonly searched types of Analytics jobs in Raleigh, NC? The most popular types of Analytics jobs in Raleigh, NC are:
What are popular job titles related to Analytics Assistant jobs in Raleigh, NC? For Analytics Assistant jobs in Raleigh, NC, the most frequently searched job titles are:
What job categories do people searching Analytics Assistant jobs in Raleigh, NC look for? The top searched job categories for Analytics Assistant jobs in Raleigh, NC are:

Technical Architect - Data, Analytics & AI

Munich Re

Durham, NC โ€ข Hybrid

$61.50 - $79.25/hr

Other

Medical, Life, Retirement, PTO

Posted 24 days ago


Job description

Location: Princeton, New Jersey Hybrid 40-50% onsiteย 

Role Overview

We are seeking aย Technical Architect (TA) with deep expertise in Data, Analytics, and Artificial Intelligence (AI) to join the IT Enterprise Architecture organization. This role is accountable for proactively leading data, analytics, and AIdriven technology transformation initiatives and enabling measurable business outcomes across the enterprise.

The Technical Architect will play a critical role inย transforming local, legacy, datadriven processes, and systems into centralized, scalable, and groupwide platforms, while ensuring alignment with enterprise architecture standards and business strategy.

Technical Architects provide technical leadership acrossย analysis, design, facilitation, and execution, supporting the evolution of enterprise Data, Analytics, and AI capabilities and the associated application portfolios and technology stacks. The role owns the creation of key architectural deliverables such as targetstate architectures, transformation roadmaps, standards, and guidelines to enable successful project delivery and longterm strategic outcomes.

This position is based in the USA and ensures that Data, Analytics, and AI architecture vision, principles, and standards are consistently executed through a common enterprise framework, with a strong emphasis on cloudbased data platforms, AI enablement, and data governance.

The ideal candidate will help advance organizational directives around simplification, modernization, and innovation by providing architectural leadership in enterprise data platforms, integration components, and AIenabled data strategies.

Key Responsibilities

  • Assist in the development of a multiyear Data, Analytics, and AI roadmap, aligned with the Munich Re Target Architecture and Roadmap Development Process, in collaboration with Data & Analytics Enterprise Architects.
  • Drive standardization of Data, Analytics, and AI technology standards, principles, and guidelines across multiple business entities.
  • Define and maintain technical standards for enterprise data management, analytics platforms, and AI enablement capabilities.
  • Design and guide datacentric and AIenabled initiatives, supporting the transition from traditional data architectures to nextgeneration cloud, analytics, and AI platforms.
  • Act as an evangelist and ambassador for enterprise architecture standards including Data Governance. Data Intake and Ingestion. Data Modeling, Data Integration, Analytics and AI lifecycle management
  • Collaborate closely with Business Solutions teams, Technology Architects, and Enterprise Data Architects across initiatives and implementations.
  • Identify technologyrelated business pain points by mapping business capabilities to current platforms, leveraging EA practices and participating in innovation activities, including AI adoption.
  • Enable IT development and infrastructure teams to make informed technology decisions through frameworks, reference architectures, standards, and reusable patterns.
  • Identify technical risks, architectural gaps, and vulnerabilities that could impact project delivery or lead to postrelease defects.
  • Reduce cost and complexity through standardization, reuse, and rationalization of data, analytics, and AI platforms.
  • Partner with EA and TA peers (enterprise, solution, and business architects) to derive the futurestate technology architecture, aligned to business strategy and external trends.
  • Define migration and transformation plans to close gaps between current and target states, in alignment with Business Solutions and Business Technology Architects.
  • Support governance, assurance, and compliance activities to ensure alignment with enterprise architecture standards and policies.
  • Assess and articulate the organizational, skills, process, and financial impact of changes to the application portfolio, data platforms, and AI stack.
  • Define and govern enterprise AI architecture standards, including model lifecycle management, MLOps, and AI platform integration.
  • Ensure responsible and compliant AI adoption, aligned with AI governance, model risk management, data privacy, and security controls.
  • Guide the integration of AI/ML capabilities into analytics platforms, including predictive, prescriptive, and generative AI use cases.
  • Collaborate with Data Science, Engineering, Security, and Risk teams to enable scalable, secure, and explainable AI solutions.
  • Establish architectural patterns for AI model deployment, monitoring, versioning, and retraining in cloud environments.
  • Evaluate emerging AI technologies, tools, and platforms and provide strategic recommendations for enterprise adoption.

ย 

Your Profile

  • 4+ years of experience in Enterprise Architecture or Technical Architecture.
  • Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, Mathematics, or Business (or equivalent).
  • Strong experience with cloud platforms and services, including:
    • Azure (e.g.; Azure AI Studio, Azure Data Services and tools)
    • AWSย  (e.g.; Amazon Bedrock, Sagemaker, Data Services and tools)
    • Databricks
  • Handson experience with enterprise data concepts, including:
    • Data Intake and Ingestion
    • Data Warehousing
    • Data Lakes / Lakehouse architectures
    • ETL / ELT
    • Interactive and operational reporting
    • Statistical and regulatory reporting
    • Master Data Management (MDM)
    • Data Governance, Quality, Security, Audit, Balance & Control
  • Solid understanding of enterprise architecture practices, including:
    • Architectural patterns
    • Roadmaps
    • Architecture Review Boards
    • Solution Design Boards
  • Experience defining data management and AI roadmaps, cloudbased services, and reusable architectural patterns.
  • Experience integrating operational data with enterprise data lakes.
  • Strong understanding of data integration challenges and solution patterns.
  • Experience with statistical and data science languages such as Python and R (strong asset).
  • Exposure to AI/ML concepts, including model development, deployment, monitoring, and MLOps (required).
  • Familiarity with Generative AI concepts, AI platforms, and enterprise adoption considerations (strong asset).
  • Strong business acumen with deep understanding of:
    • Financial systems
    • Corporate and backoffice systems
    • Enterprise data management, analytics, and AI technology landscape
  • Strong problemsolving skills, unquestioned integrity, and high collaboration capability.
  • Passion for innovation, continuous improvement, modernization, and change management.
  • Excellent written and verbal communication skills, with the ability to communicate effectively at all levels.
  • High sense of ownership, accountability, and pride in delivered outcomes.

At Munich Re US, we see Diversity and Inclusion as a solution to the challenges and opportunities all around us. Our goal is to foster an inclusive culture and build a workforce that reflects the customers we serve and the communities in which we live and work. We strive to provide a workplace where all of our colleagues feel respected, valued and empowered to achieve their very best every day. We recruit and develop talent with a focus on providing our customers the most innovative products and services.

We are an equal opportunity employer. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

The Company is open to considering candidates in Princeton, NJ. The salary range posted below applies to the Company's Princeton location.

The base salary range anticipated for this position isย $141,800 - $207,900ย plus opportunity for company bonus based upon a percentage of eligible pay.ย  In addition, the company makes available a variety of benefits to employees, including health insurance coverage, an employee wellness program, life and disability insurance, 401k match, retirement savings plan, paid holidays and paid time off (PTO).ย 

The salary estimate displayed represents the typical salary range for candidates hired in this position in Princeton. Factors that may be used to determine your actual salary include your specific skills, how many years of experience you have and comparison to other employees already in this role. Most candidates will start in the bottom half of the range.ย