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Entry Level Data Extraction Jobs (NOW HIRING)

SC Works Trident

Data Scientist /data analyst entry level /AI /software programmer(Remote) Occupation: Data ... Apply data mining, data modeling, natural language processing, and machine learning to extract and ...

AA2IT

Data Entry - SAP

Lubbock, TX · On-site

$20/hr

This is an entry level position. Responsibilities: Supply Data Entry Lubbock, TX This position ... Other Mastery of desk top tools to perform data extractions/downloads from SAP, creates BW and ...

University of Utah

Data Scientists

Campus, IL · On-site

This is an Entry-Level position in the General Professional track. Job Code: P33861 Grade: P16 Data ... extraction from the data. Generate and test hypotheses and analyze and interpret the results of ...

University of Utah

Data Scientists

Campus, IL

This is an Entry-Level position in the General Professional track. Job Code: P33861 Grade: P16 Data ... extraction from the data. Generate and test hypotheses and analyze and interpret the results of ...

University of Utah

Data Scientists

Campus, IL · On-site

This is an Entry-Level position in the General Professional track. Job Code: P33861 Grade: P16 Data ... extraction from the data. Generate and test hypotheses and analyze and interpret the results of ...

University of Utah

Data Scientists

Salt Lake City, UT · On-site

$75K - $105K/yr

This is an Entry-Level position in the General Professional track. Job Code: P33861 Grade: P16 Data ... extraction from the data. Generate and test hypotheses and analyze and interpret the results of ...

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How much do entry level data extraction jobs pay per hour?

As of Sep 9, 2026, the average hourly pay for entry level data extraction in the United States is $20.24, according to ZipRecruiter salary data. Most workers in this role earn between $16.35 and $21.88 per hour, depending on experience, location, and employer.

What is an entry level data extraction?

An Entry Level Data Extraction job involves collecting, organizing, and processing data from various sources, such as documents, websites, or databases. People in this role typically use basic tools and software to extract relevant information, ensuring its accuracy and completeness. These positions are suitable for individuals new to the field and often require attention to detail, basic computer skills, and sometimes familiarity with data management tools. Entry level data extraction jobs serve as a starting point for careers in data analysis and data management.

What are the key skills and qualifications needed to thrive as an entry level data extraction specialist?

To thrive as an Entry Level Data Extraction specialist, you need strong attention to detail, basic data analysis skills, and familiarity with spreadsheets or databases, often supported by a high school diploma or equivalent. Commonly used tools include Microsoft Excel, Google Sheets, and sometimes data extraction software or simple scripting languages like Python. Strong organizational skills, problem-solving abilities, and effective communication help you excel in handling large volumes of information and clarifying data requirements. These skills ensure accuracy, efficiency, and reliability in preparing and delivering data critical for business decisions.

What are some common challenges faced in an entry level data extraction role, and how can they be addressed?

Entry level data extraction professionals often encounter challenges such as dealing with inconsistent data formats, handling large volumes of unstructured information, and learning new data extraction tools or software. Addressing these challenges involves developing strong attention to detail, collaborating closely with team members to share best practices, and proactively seeking training opportunities to build technical skills. Regular communication with supervisors and peers can also help in troubleshooting issues and improving workflow efficiency.

What is the difference between Entry Level Data Extraction vs Data Analyst?

AspectEntry Level Data ExtractionData Analyst
Required CredentialsHigh school diploma or equivalent; basic knowledge of data toolsBachelor's degree in data science, statistics, or related field
Work EnvironmentData collection, cleaning, and initial processing; often in data-focused teamsData analysis, interpretation, reporting; often in cross-functional teams
Employer & Industry UsageUsed in tech, finance, marketing for data gathering tasksUsed across industries for insights, decision-making, and reporting

Entry Level Data Extraction involves gathering and preparing data for analysis, requiring basic technical skills. Data Analysts build on this foundation, performing in-depth analysis, interpretation, and reporting. While data extraction is a starting point, data analysis involves a broader skill set and strategic insights.

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Entry Level Data Extraction jobs near you
Infographic showing various Entry Level Data Extraction job openings in the United States as of September 2026, with employment types broken down into 50% Full Time, and 50% Part Time. Highlights an 100% In-person job distribution, with an average salary of $42,098 per year, or $20.2 per hour.

Software Engineer I, Data Science (New Grad)

Denver, CO • On-site

True Anomaly
Guided Missile and Space Vehicle Manufacturing • 11 - 50 employees
Learn more about True Anomalyexternal

$117K - $141K/yr

Full-time

Posted 16 days ago

Key responsibilities

  • Perform exploratory data analysis on manufacturing telemetry, test logs, mission data, and on-orbit spacecraft health telemetry to identify patterns and surface anomalies

  • Build operational dashboards in Grafana or Plotly Dash showing real-time production status, spacecraft health metrics, mission performance, and anomaly alerts

  • Train basic predictive models (logistic regression, random forests) to flag at-risk components during manufacturing and predict spacecraft health degradation during missions

Job description

Space is a warfighting domain. True Anomaly seeks those with the talent and ambition to build the technology that secures it.
OUR MISSION
True Anomaly delivers decisive capabilities for space superiority. We build autonomous spacecraft, advanced payloads, mission software, and space-based interceptors - enabling the U.S. and its Allies to secure the space environment and counter threats from the ultimate high ground.
OUR VALUES
  • Be the offset. We create asymmetric advantages with creativity and ingenuity.
  • What would it take? We challenge assumptions to deliver ambitious results.
  • It's the people. Our team is our competitive advantage and we are better together.

YOUR MISSION
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You'll turn spacecraft data into actionable insights across manufacturing and operations: building dashboards that surface production bottlenecks and on-orbit anomalies, analyzing test failures and mission telemetry to identify root causes, training predictive models that flag at-risk components before integration and detect spacecraft health degradation during missions, and mining telemetry to catch anomalies operators would miss. Your work spans the full spacecraft lifecycle. Pre-launch, you'll analyze manufacturing telemetry, test logs, failure reports, and supplier data to catch problems before integration. Post-launch, you'll monitor on-orbit telemetry streams, detect anomalies in spacecraft health data, analyze mission performance, and flag degradation patterns that predict future failures. This is entry-level data science work supporting hardware production and spacecraft operations. You'll write SQL queries, build predictive models in Python, create operational dashboards, and see your analysis drive decisions on the manufacturing floor and in mission control.
This is a 3 month temporary employment engagement. There is potential to convert to regular employment based on performance and business need.
RESPONSIBILITIES
  • Perform exploratory data analysis on manufacturing telemetry, test logs, mission data, and on-orbit spacecraft health telemetry to identify patterns and surface anomalies
  • Build operational dashboards in Grafana or Plotly Dash showing real-time production status, spacecraft health metrics, mission performance, and anomaly alerts
  • Train basic predictive models (logistic regression, random forests) to flag at-risk components during manufacturing and predict spacecraft health degradation during missions
  • Write SQL queries to extract, join, and aggregate data from manufacturing databases, test systems, mission telemetry streams, and spacecraft health archives
  • Analyze test failures and on-orbit anomalies to identify common failure modes, cluster similar issues, and quantify impact on schedule and mission success
  • Create data visualizations (matplotlib, seaborn, Plotly) that communicate findings to engineers, manufacturing leads, mission operators, and program managers
  • Implement statistical process control charts to detect out-of-spec conditions in manufacturing processes and spacecraft telemetry before they cascade
  • Monitor on-orbit telemetry streams for anomalies: battery voltage trends, thermal behavior, attitude control health, communications link quality
  • Document analysis methodology in Jupyter notebooks enabling reproducibility and knowledge transfer across manufacturing and operations teams
  • Learn reliability engineering and mission operations concepts: failure modes, burn-in testing, on-orbit commissioning, spacecraft health monitoring, and anomaly response procedures

QUALIFICATIONS
  • Bachelor's or Master's degree in data science, statistics, industrial engineering, applied mathematics, operations research, or related quantitative field
  • Proficiency in Python for data analysis: pandas, numpy, matplotlib, seaborn
  • Working knowledge of SQL for querying relational databases: SELECT, JOIN, GROUP BY, aggregation functions
  • Coursework in statistics: hypothesis testing, regression, probability distributions, experimental design
  • Ability to create clear visualizations that communicate insights to technical and non-technical audiences
  • Strong curiosity about how things fail and how data can predict failures before they happen
  • Debugging mindset: when the model gives wrong answers or the query returns unexpected results, you dig in to find out why
  • Eagerness to learn manufacturing, operations, and reliability engineering domains where data drives real decisions
  • U.S. Citizen (required for facility access and government contracts)

PREFERRED SKILLS AND EXPERIENCE
  • Experience with machine learning in Python: scikit-learn for classification/regression, model validation, train/test splits, cross-validation
  • Familiarity with time-series analysis: plotting sensor trends, detecting change points, smoothing noisy signals
  • Exposure to data visualization tools: Grafana, Tableau, Plotly Dash, or similar dashboard frameworks
  • Understanding of basic reliability concepts: failure rates, survival curves, mean time between failures (MTBF)
  • Prior internship or project analyzing real-world operational data: manufacturing, logistics, quality control, IoT sensor data
  • Experience with version control (git) and collaborative data analysis workflows
  • Coursework or projects in industrial engineering, operations research, or quality management
  • Familiarity with data cleaning and wrangling: handling missing values, outlier detection, data quality assessment
  • Understanding of experimental design: A/B testing, randomized controlled trials, confounding variables
  • Exposure to anomaly detection techniques: z-scores, control charts, boxplot analysis
  • Prior work with manufacturing or hardware production data (even from coursework or academic projects)
  • Familiarity with Jupyter notebooks, literate programming, and reproducible analysis practices

COMPENSATION
  • Base Salary: Denver: $75,000; Long Beach: $80,000

ADDITIONAL REQUIREMENTS
  • Work Location-Successful candidates will be located near Denver or Colorado Springs. While we observe a hybrid work environment, some work must be done on site.
  • Work environment-the work environment; temperature, noise level, inside or outside, or other factors that will affect the person's working conditions while performing the job.
  • Physical demands-the physical demands of the job, including bending, sitting, lifting and driving.

This position will be open until it is successfully filled. To submit your application, please follow the directions below. #LI-Onsite
To conform to U.S. Government space technology export regulations, including the International Traffic in Arms Regulations (ITAR) you must be a U.S. citizen, lawful permanent resident of the U.S., protected individual as defined by 8 U.S.C. 1324b(a)(3), or eligible to obtain the required authorizations from the U.S. Department of State.
True Anomaly is committed to equal employment opportunity on any basis protected by applicable state and federal laws. If you have a disability or additional need that requires accommodation, please do not hesitate to let us.

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