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Entry Level Web Scraping Jobs (NOW HIRING)

The entry level position supports the core team by conducting the following activities: hands ... Scraping laminator top and side plates Dry end start up, shut down and running out the board ...

Entry Level Web Scraping information

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$32K

$94.1K

$161.5K

How much do entry level web scraping jobs pay per year?

As of Aug 20, 2026, the average yearly pay for entry level web scraping in the United States is $94,149.00, according to ZipRecruiter salary data. Most workers in this role earn between $63,000.00 and $101,500.00 per year, depending on experience, location, and employer.

What is an entry level web scraping job?

Entry level web scraping jobs involve collecting data from websites using automated tools or scripts, often written in programming languages like Python. These roles typically require basic coding skills and familiarity with libraries such as BeautifulSoup, Scrapy, or Selenium. Entry level web scrapers may be tasked with extracting specific information, cleaning and formatting data, and ensuring that their methods comply with website terms of service. Many positions offer on-the-job training and are a great way to build experience in data analysis and automation.

What are the key skills and qualifications needed to thrive as an entry level web scraping professional?

To excel as an Entry Level Web Scraping professional, you need a solid understanding of programming languages like Python, basic knowledge of HTML/CSS, and familiarity with data extraction concepts. Experience with tools such as BeautifulSoup, Scrapy, or Selenium, and a grasp of using APIs or regular expressions, is typically required. Attention to detail, problem-solving, and persistence are valuable soft skills for overcoming web structure changes and handling large datasets. These skills ensure efficient, accurate data collection and adaptability in meeting the evolving needs of data-driven projects.

What are some common challenges faced by entry level web scraping professionals, and how can they be addressed?

Entry level web scraping professionals often encounter challenges such as navigating websites with dynamic content, handling anti-scraping mechanisms like CAPTCHAs, and ensuring data accuracy. Overcoming these obstacles typically involves learning to use tools like Selenium for dynamic sites, implementing proper request headers, and respecting website terms of service. Collaborating with more experienced developers or data engineers on your team can provide valuable guidance, while continuous learning of best practices helps you grow in the role.

What is the difference between Entry Level Web Scraping vs Data Analyst?

AspectEntry Level Web ScrapingData Analyst
Required CredentialsBasic programming skills, knowledge of web technologiesDegree in statistics, data science, or related field
Work EnvironmentPrimarily technical, focused on coding and data extractionAnalytical, reporting, and interpreting data for decision-making
Employer & Industry UsageTech companies, market research, e-commerceFinance, healthcare, marketing, consulting
Common Search & Comparison IntentUnderstanding entry-level data extraction rolesComparing data analysis and data scraping roles

Entry Level Web Scraping involves basic programming and web technology skills to extract data from websites, often used in tech and e-commerce sectors. Data Analysts focus on interpreting data, requiring statistical knowledge and often a degree in related fields. While both roles handle data, web scraping is more technical and coding-focused, whereas data analysis emphasizes data interpretation and reporting.

More about Entry Level Web Scraping jobs

What cities are hiring for Entry Level Web Scraping jobs?

Cities with the most Entry Level Web Scraping job openings:

What are the most commonly searched types of Web Scraping jobs?

The most popular types of Web Scraping jobs are:

Infographic showing various Entry Level Web Scraping job openings in the United States as of August 2026, with employment types broken down into 1% Internship, 80% Full Time, 11% Part Time, 1% Temporary, and 7% Contract. Highlights an 82% Physical, 4% Hybrid, and 14% Remote job distribution, with an average salary of $94,149 per year, or $45.3 per hour.

DATA SCIENTIST I-FINANCIAL & TIME SERIES FORECASTING

VSolvit

Norco, CA • On-site

$34.62 - $45.67/hr

Full-time

Medical, Dental, Vision, Life, Retirement

Posted 9 days ago


Job description

Job Summary

We are seeking a talented and driven Data Scientist to join our evolving and dynamic team. This position is open to candidates at entry level of experience who possess a strong mathematical foundation and a passion for predictive modeling. In this role, you will build, validate, and maintain multi-variable time series forecasting models to project financial data and agency expenditures over multi-year horizons. You will work directly with financial records, taking ownership of the data lifecycle, from scraping, joining, and transforming raw datasets to rigorous model validation. We are looking for a resourceful problem-solver who excels at mathematical modeling, adapts quickly to changing data environments, and ensures our predictive tools remain accurate and resilient.

As with any position, additional expectations exist. Some of these are, but are not limited to, adhering to normal working hours, meeting deadlines, following company policies as outlined by the Employee Handbook, communicating regularly with assigned supervisor(s), and staying focused on the assigned tasks including company meetings, and completing other tasks as assigned.

Responsibilities

  • Time Series & Mathematical Modeling: Support the development and evaluation of statistical and time series forecasting models, including ARIMA, Prophet, regression, and tree-based models.
  • Data Pipeline Construction & Scripting: Write and maintain Python scripts to scrape, extract, clean, join, and transform structured and unstructured financial data from web sources, APIs, databases, and raw files.
  • Model Validation & Quality Assurance: Execute established validation workflows, compare model performance using metrics such as RMSE, MAE, and MAPE, and identify potential data-quality or data-leakage issues.
  • Quantitative Feature Engineering: Assist with analyzing historical pricing, inflation indices, budget cycles, and spending patterns to create features for forecasting models.
  • Data Analysis & Documentation: Perform exploratory data analysis and document data sources, assumptions, transformations, model results, and known limitations.
  • Stakeholder Communication: Create reports, visualizations, and summaries that explain analytical findings to technical and non-technical stakeholders.
  • Resourcefulness & Learning: Learn new domain requirements, proprietary databases, customer tools, and forecasting methods with guidance from senior team members.
  • Compliance & Security: Maintain strict compliance with defense security protocols, confidentiality guidelines, and internal data handling policies.

Basic Qualifications

US Citizenship Required

Ability to obtain and maintain a Secret Security Clearance

  • Bachelor’s degree in Mathematics, Statistics, Computer Science, Data Science, Economics, Finance, Engineering, or a related quantitative field.
  • Recent graduates and candidates with up to two years of relevant professional, internship, research, or academic experience are encouraged to apply.
  • Foundational knowledge of linear algebra, calculus, probability, and statistics.
  • Working knowledge of Python for data manipulation and analysis, including pandas and NumPy.
  • Academic, internship, research, or project experience involving statistical modeling, machine learning, predictive analytics, or time series forecasting.
  • Basic understanding of single-variable and multi-variable forecasting methods.
  • Understanding of model evaluation concepts, including training and test datasets, error metrics, overfitting, and data leakage.
  • Strong attention to detail and the ability to organize, document, and communicate analytical work.
  • Strong verbal and written communication skills with the ability to explain technical concepts clearly.
  • If applicable: If you are or have been recently employed by the U.S. government, a post-employment ethics letter will be required if employment is offered.

Preferred Skills and Qualifications

  • Coursework, internship, research, or project experience in Economics, Finance, Econometrics, Accounting, or time series analysis.
  • Experience with scikit-learn, statsmodels, Prophet, matplotlib, or similar analytical libraries.
  • Familiarity with SQL, APIs, web scraping, ETL processes, or data-processing tools.
  • Experience completing a capstone, thesis, internship, or personal project involving forecasting or predictive modeling.
  • Exposure to government, defense, budgeting, or financial datasets.
  • Familiarity with inflation adjustments, budget cycles, fiscal years, and macroeconomic factors.
  • Familiarity with version control tools such as Git or GitHub.
  • Continued education and interest in current and emerging AI/ML technologies.
  • Strong problem-solving skills and the ability to work in a fast-paced environment.

Company Summary

Join the VSolvit Team! Founded in 2006, VSolvit (pronounced 'We Solve It') is a technology services provider that specializes in cybersecurity, cloud computing, geographic information systems (GIS), business intelligence (BI) systems, data warehousing, engineering services, and custom database and application development. VSolvit is an award winning WOSB, CA CDB, MBE, WBE, and CMMI Level 3 certified company. We offer a customizable health benefits program that best meets the needs of its employees. Offering may include: medical, dental, and vision insurance, life insurance, long and short-term disability and other insurance products, Health Savings Account, Flexible Spending Account, 401K Retirement Plan options, Tuition Reimbursement, and assorted voluntary benefits. Our goal is to grow together and enjoy the work that we do as a team.


VSolvit LLC is an Equal Opportunity/Affirmative Action employer and will consider all qualified applicants for employment without regard to race, color, religion, sex, national origin, protected veteran status, or disability status