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Large Dataset Jobs (NOW HIRING)

The Judge Group

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Security Controls Analyst

Chandler, AZ · On-site

$50 - $55/hr

Large dataset analysis * Advanced formulas * Pivot tables * Reporting and data visualization * Hands-on Jira experience , including: * * Workflow management * Ticket tracking and processing * Kanban ...

New

Kaiser Aluminum

Metallurgical Engineer

Spokane, WA · On-site

$85K - $150K/yr

Production process data collection, high dimension large dataset multivariate analysis, classic and penalized regression predictive modelling, advanced neural-network and decision-tree based ...

Apple

NAND Q&R Engineer

Cupertino, CA · On-site

Experience with statistical data analysis and large dataset interpretation.Experience in NAND qual testing, failure analysis and/or debugging. MS or PhD in a technical discipline with 3+ years of ...

Lumafield

Backend Software Engineer

San Francisco, CA · On-site

$125K - $140K/yr

Experience with large dataset processing using numpy * Strong software engineering fundamentals including git, unit testing, pull request reviews, module/interface design, and applications using ...

Apple

NAND Q&R Engineer

Cupertino, CA · On-site

Experience with statistical data analysis and large dataset interpretation.Experience in NAND qual testing, failure analysis and/or debugging. MS or PhD in a technical discipline with 10+ years of ...

Lumafield

Backend Software Engineer

San Francisco, CA · On-site

$125K - $140K/yr

Experience with large dataset processing using numpy > * Strong software engineering fundamentals including git, unit testing, pull request reviews, module/interface design, and applications using ...

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Large Dataset information

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$47K

$98.6K

$140.5K

How much do large dataset jobs pay per year?

As of Jun 7, 2026, the average yearly pay for large dataset in the United States is $98,572.00, according to ZipRecruiter salary data. Most workers in this role earn between $84,000.00 and $113,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Data Scientist working with large datasets, and why are they important?

To thrive as a Data Scientist handling large datasets, you need strong analytical skills, proficiency in statistics, and a background in computer science or a related field. Expertise in programming languages like Python or R, familiarity with big data frameworks (such as Hadoop or Spark), and experience using data visualization tools are typically required. Strong problem-solving ability, attention to detail, and effective communication skills help in translating complex data findings into actionable insights. These skills are essential for extracting meaningful information from massive datasets, supporting data-driven decision-making, and driving business value.

What is the difference between Large Dataset vs Data Analyst?

AspectLarge DatasetData Analyst
Required CredentialsOften no formal degree, but knowledge of data managementBachelor's degree in data science, statistics, or related field
Work EnvironmentData storage, database management, data processingData interpretation, reporting, visualization
Industry UsageUsed across industries for storing and managing dataApplied in business, finance, healthcare for analysis
Search & Comparison IntentUnderstanding data volume managementAnalyzing data to generate insights

Large Dataset refers to the volume of data stored and managed, often requiring data engineering skills. Data Analysts focus on interpreting and visualizing data to support decision-making. While large datasets are the raw material, data analysts turn that data into actionable insights.

What are large datasets?

Large datasets are collections of data that are so vast in size or complexity that traditional data processing software struggles to manage, process, or analyze them efficiently. They are often associated with 'big data' and can include structured, semi-structured, or unstructured data from sources such as social media, sensors, business transactions, and more. Handling large datasets typically requires specialized tools and techniques for storage, computation, and analysis, such as distributed computing frameworks like Hadoop or Spark. These datasets are crucial in fields like data science, machine learning, and analytics, enabling deeper insights and data-driven decision-making.

What are some common challenges when working with large datasets, and how can professionals overcome them?

Professionals handling large datasets often face challenges such as ensuring data quality, managing storage and processing constraints, and optimizing data retrieval times. To overcome these, it's important to leverage scalable data storage solutions, such as distributed databases or cloud platforms, and utilize data processing frameworks like Hadoop or Spark. Regular data validation, efficient indexing, and collaborating closely with data engineers and analysts can also help maintain accuracy and streamline workflows.
Infographic showing various Large Dataset job openings in the United States as of May 2026, with employment types broken down into 1% As Needed, 91% Full Time, and 8% Part Time. Highlights an 79% Physical, 6% Hybrid, and 15% Remote job distribution, with an average salary of $98,572 per year, or $47.4 per hour.
Security Controls Analyst

Security Controls Analyst

The Judge Group

Chandler, AZ • On-site

$50 - $55/hr

Contractor

Medical, Dental, Vision, Retirement

Posted 2 days ago

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Job description

Information Security Controls Analyst

Chandler, AZ (Hybrid Onsite 3 days per week)

Contract with Conversion Opportunity

$50-$55 HR W2


Available for W‐2 employees only. We are not accepting C2C or 1099 arrangements.



Job Summary

We are seeking an Information Security Controls Analyst to support the execution of a critical enterprise security control. This role plays a key part in ensuring continuity, accuracy, and effectiveness of control execution through strong data analysis, workflow management, and cross‐functional collaboration. The ideal candidate is highly organized, analytical, and an effective communicator.



Key Responsibilities

  • Execute and support enterprise information security controls in alignment with organizational policies
  • Analyze and manage large datasets using Microsoft Excel to produce reports, metrics, and insights
  • Track, manage, and resolve work items using Jira Kanban boards
  • Monitor control execution activities and ensure timely completion
  • Collaborate with application managers, business partners, architects, analysts, and engineering teams
  • Communicate status, risks, and findings clearly through written and verbal updates
  • Utilize Microsoft Teams and SharePoint to document, organize, and share control artifacts


Required Qualifications

  • Advanced Microsoft Excel skills, including:
    • Large dataset analysis
    • Advanced formulas
    • Pivot tables
    • Reporting and data visualization
  • Hands-on Jira experience, including:
    • Workflow management
    • Ticket tracking and processing
    • Kanban boards
  • Strong cross-functional communication skills, with the ability to work effectively across technical and business teams
  • Experience supporting control execution, audit, compliance, or operational risk activities
  • Strong written and verbal communication skills


Preferred Qualifications

  • Experience validating and maintaining information security controls
  • Familiarity with financial services environments (nice to have, not required)


Tools & Technologies

  • Microsoft Excel (advanced)
  • Jira (Kanban)
  • Microsoft Teams
  • SharePoint