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Entry Level Data Science Jobs in Anaheim, CA (NOW HIRING)

Management Information Systems, Computer and Information Science, Systems Engineering, Mathematics ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

Management Information Systems, Computer and Information Science, Systems Engineering, Mathematics ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

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Entry Level Data Science information

See Anaheim, CA salary details

$11

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$28

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

As of Aug 29, 2026, the average hourly pay for entry level data science in Anaheim, CA is $19.95, according to ZipRecruiter salary data. Most workers in this role earn between $16.88 and $22.40 per hour, depending on experience, location, and employer.

What is an entry level data scientist?

Entry level data science jobs are positions designed for individuals who are starting their careers in the field of data science, often requiring minimal professional experience. These roles typically involve working with data collection, cleaning, and analysis, as well as assisting more senior data scientists with projects. Entry level data scientists are expected to have a foundational understanding of statistics, programming (often in Python or R), and basic machine learning concepts. They may work in various industries, helping organizations gain insights from data to support decision-making.

What types of projects or tasks can I expect to work on as an entry level data scientist?

As an entry-level data scientist, you'll typically work on tasks such as data cleaning, exploratory data analysis, and supporting the development of predictive models. You may also assist in preparing datasets, generating reports, and visualizing data for stakeholders. Collaboration with more senior data scientists and cross-functional teams like engineering or business analysts is common, giving you opportunities to learn and grow your technical and communication skills. These foundational projects are essential for building your expertise and preparing for more complex responsibilities as you advance in your career.

What are the key skills and qualifications needed to thrive as an entry level data scientist, and why are they important?

To thrive as an Entry Level Data Scientist, you need a strong background in statistics, programming (often Python or R), and data analysis, typically supported by a relevant degree such as computer science, mathematics, or statistics. Familiarity with technical tools like SQL databases, data visualization software (e.g., Tableau), and machine learning libraries (such as scikit-learn or TensorFlow) is commonly expected. Curiosity, problem-solving ability, and effective communication help you interpret data insights and collaborate with diverse teams. These skills ensure you can extract meaningful insights from data, contribute to data-driven decision-making, and grow within the analytics field.

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

AspectEntry Level Data ScienceData Analyst
Required CredentialsBachelor's in CS, Statistics, or related field; some certificationsBachelor's in Business, Statistics, or related field; certifications optional
Work EnvironmentTech companies, startups, research labsBusiness, marketing, finance sectors
Employer & Industry UsageData-driven roles in tech and researchBusiness insights, reporting, and visualization
Common Search & ComparisonYesYes

Entry Level Data Science and Data Analyst roles often share similar educational backgrounds and work environments. However, data scientists typically focus on building models and advanced analytics, while data analysts concentrate on interpreting data and creating reports. Both roles are essential in data-driven organizations, but they differ in technical complexity and scope.

Are there entry-level data science roles?

Yes, entry-level data science roles are available and typically require foundational skills in programming, statistics, and data analysis, often using tools like Python or R. These positions are suitable for recent graduates or those transitioning into data science and may involve internships or junior analyst roles to gain experience.

How to start a career in entry level data science with no experience?

To start a career in entry level data science with no experience, focus on building foundational skills in programming languages like Python or R, and learn data analysis and visualization tools such as SQL and Tableau. Completing online courses, earning certifications, and working on personal projects or internships can demonstrate your abilities to employers and help you gain practical experience.

What are the most commonly searched types of Data Science jobs in Anaheim, CA?

The most popular types of Data Science jobs in Anaheim, CA are:

What are popular job titles related to Entry Level Data Science jobs in Anaheim, CA?

For Entry Level Data Science jobs in Anaheim, CA, the most frequently searched job titles are:

What job categories do people searching Entry Level Data Science jobs in Anaheim, CA look for?

The top searched job categories for Entry Level Data Science jobs in Anaheim, CA are:

What cities near Anaheim, CA are hiring for Entry Level Data Science jobs?

Cities near Anaheim, CA with the most Entry Level Data Science job openings:

Infographic showing various Entry Level Data Science job openings in Anaheim, CA as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 13% Part Time, and 2% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $41,488 per year, or $19.9 per hour.

DATA SCIENTIST I-FINANCIAL & TIME SERIES FORECASTING

Norco, CA โ€ข On-site

VSolvit
IT Servicesย โ€ขย 201 - 500 employees

$34.62 - $45.67/hr

Full-time

Medical, Dental, Vision, Life, Retirement

Posted 19 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