ZipRecruiter

Log In

2

No Experience Data Science Jobs in Riverside, CA

Hireblazer

Senior Data Scientist

Irvine, CA · On-site

Experience developing analytics with machine learning, deep learning, NLP, and/or other related ... Master's or Ph.D. degree in Computer Science, Applied Mathematics, (Bio) Statistics, Applied ...

Boot Barn

Data Scientist

Irvine, CA · On-site

... data science best practices, model documentation, and the creation of reusable modeling frameworks. • Translate complex model results into clear business insights for technical and non-technical ...

San Manuel Casino

Data Engineer

Highland, CA

$113K - $136K/yr

There are no hybrid or remote positions available. ESSENTIAL DUTIES AND RESPONSIBILITIES 1. ... EDUCATION, EXPERIENCE AND QUALIFICATIONS * Bachelor's degree in data science, Data Analytics ...

New

Yuhaaviatam of San Manuel Nation

Data Engineer

Highland, CA · On-site

$113K - $136K/yr

There are no hybrid or remote positions available. ESSENTIAL DUTIES AND RESPONSIBILITIES 1. ... EDUCATION, EXPERIENCE AND QUALIFICATIONS * Bachelor's degree in data science, Data Analytics ...

New

San Manuel Band of Mission Indians

Data Engineer

Highland, CA · On-site

$113K - $136K/yr

EDUCATION, EXPERIENCE AND QUALIFICATIONS * Bachelor's degree in data science, Data Analytics, Statistics, Data Management, Business, Economics, Finance, Accounting, Mathematics, or related field ...

New

next page

Showing results 1-20

All JobsData Science JobsNo Experience Data Science JobsNo Experience Data Science Jobs in Riverside, CA

No Experience Data Science information

See Riverside, CA salary details

$39.1K

$128K

$205K

How much do no experience data science jobs pay per year?

As of Jul 13, 2026, the average yearly pay for no experience data science in Riverside, CA is $128,049.00, according to ZipRecruiter salary data. Most workers in this role earn between $102,800.00 and $141,900.00 per year, depending on experience, location, and employer.

What key skills and qualifications are needed to succeed in an entry-level Data Science role with no prior experience, and why are they important?

To thrive in an entry-level Data Science role, foundational knowledge of statistics, programming (often in Python or R), and data analysis is essential, usually supported by a relevant degree or completion of online courses. Familiarity with tools such as Jupyter Notebooks, SQL databases, and introductory machine learning libraries like scikit-learn is typically expected. Curiosity, problem-solving abilities, and effective communication help newcomers stand out by enabling them to learn quickly and explain insights clearly. These skills and qualities are crucial for accurately analyzing data, collaborating with teams, and delivering actionable results as you build your experience.

What is the difference between No Experience Data Science vs Data Analyst?

AspectNo Experience Data ScienceData Analyst
Required CredentialsEntry-level, often no certifications neededOften requires a degree in related field; certifications like Excel or SQL helpful
Work EnvironmentStartups, internships, or entry-level roles in tech or financeCorporate offices, consulting firms, or government agencies
Industry UsageGrowing in tech, finance, healthcare, and marketingWidely used across industries for data interpretation and reporting
Search & Comparison IntentPeople seeking entry-level data roles with minimal experienceIndividuals comparing entry-level data roles in analytics

While No Experience Data Science roles focus on entry-level positions with minimal prior skills, Data Analysts typically require some foundational knowledge and relevant certifications. Both roles are common in various industries, but Data Analysts often have more defined responsibilities in data interpretation and reporting. Understanding these differences helps job seekers target the right roles based on their experience level and career goals.

What entry-level tasks or projects can someone without experience expect in a data science role?

In an entry-level data science position, especially for those without prior experience, you can expect to start with foundational tasks such as data cleaning, exploratory data analysis, and assisting in data collection processes. You may also help maintain documentation, prepare data visualizations, and support more senior team members with basic statistical analysis or model evaluation. These responsibilities not only build your technical skills but also expose you to the real-world workflows and collaborative problem-solving typical of data science teams.

What is the 80 20 rule in data science?

In data science, the 80/20 rule suggests that roughly 80% of results come from 20% of efforts or features. Data scientists often focus on the most impactful variables or tasks to optimize model performance and efficiency.

What are 'No Experience Data Science' jobs?

'No Experience Data Science' jobs are entry-level positions in the field of data science that do not require prior professional experience. These roles are designed for recent graduates, career changers, or individuals looking to start a career in data science. They typically focus on foundational skills such as data cleaning, basic statistical analysis, and simple data visualization. Employers may provide training and mentorship to help new hires gain practical experience. Common job titles include Data Science Intern, Junior Data Analyst, or Data Science Trainee.

Is it possible to get a data science job with no experience?

Entry-level data science positions often do not require prior professional experience if candidates have relevant skills such as programming in Python or R, knowledge of statistics, and familiarity with data analysis tools. Building a portfolio through personal projects, online courses, or certifications can improve chances of securing such roles without formal work experience.

Is 30 too late for data science?

No, 30 is not too late to start a career in data science. Many professionals transition into data science in their 30s or later by acquiring relevant skills such as programming, statistics, and machine learning through online courses or bootcamps, and building a portfolio of projects. Age is less important than skills, experience, and continuous learning in this field.

How do I become a data scientist with no experience?

To become a data scientist with no experience, focus on building foundational skills in programming (Python or R), statistics, and data analysis through online courses and tutorials. Gain practical experience by working on projects, participating in competitions, and learning tools like SQL, machine learning frameworks, and data visualization software. Earning certifications or completing a relevant bootcamp can also improve your prospects and demonstrate your skills to employers.
What are the most commonly searched types of Data Science jobs in Riverside, CA? The most popular types of Data Science jobs in Riverside, CA are:
What are popular job titles related to No Experience Data Science jobs in Riverside, CA? For No Experience Data Science jobs in Riverside, CA, the most frequently searched job titles are:
What job categories do people searching No Experience Data Science jobs in Riverside, CA look for? The top searched job categories for No Experience Data Science jobs in Riverside, CA are:
What cities near Riverside, CA are hiring for No Experience Data Science jobs? Cities near Riverside, CA with the most No Experience Data Science job openings:
No Experience Data Science jobs near you
Infographic showing various No Experience Data Science job openings in Riverside, CA as of July 2026, with employment types broken down into 13% Internship, 74% Full Time, and 13% Part Time. Highlights an 62% In-person, and 38% Remote job distribution, with an average salary of $128,049 per year, or $61.6 per hour.
Data Scientist-Direct Hire

Data Scientist-Direct Hire

US Department of the Treasury

Santa Ana, CA • On-site

$74K/yr

Other

Posted 7 days ago

New

U.S. Department Of The Treasury rating

8.2

Company rating: 8.2 out of 10

Based on 13 frontline employees who took The Breakroom Quiz

235th of 691 rated public administrative organizations

Job description

WHAT IS DATA AND ANALYTICS (DAO)-RESEARCH, APPLIED ANALYTICS & STATISTICS (RAAS)?
A description of the business units can be found at: https://www.jobs.irs.gov/about/who/business-divisions

  • Position(s) are to be filled in the following area(s):
    • DAO - DATA AND ANALYTICS
  • Consider each location carefully when applying. If you are selected for a location, that location will become your official post of duty.
REVIEW THE ADDITIONAL INFORMATION BELOW FOR FURTHER DETAILSQualifications:Federal experience is not required. Experience may have been gained in the public sector, private sector or through Volunteer Service. One year of experience refers to full-time work; part-timework is considered on a prorated basis. To ensure full credit for your work experience, please indicate dates of employment by month/day/year, and indicate number of hours worked per week, on your resume.
You must meet the following requirements by the cut-off dates as shown in announcement under the 'How to Apply' section.
QUALIFICATION REQUIREMENTS: To qualify for this position, you must meet the qualification requirements outlined below:
BASIC REQUIREMENTS All GRADES: EDUCATION:
You must have a bachelor's or higher degree in mathematics, statistics, computer science, data science or other field directly related to the position. The degree must be in a major field of study (at least at the baccalaureate level) that is appropriate for the position.
OR
COMBINATION OF EDUCATION AND EXPERIENCE: You may qualify with an equivalent combination of qualifying experience and education with at least 30 semester hours related to Mathematics, statistics, computer science, data science or field directly related to the position. The degree must be in a major field of study (at least at the baccalaureate level) that is appropriate for the position.
EDUCATION/SPECIALIZED EXPERIENCE FOR GS-11: In addition to meeting basic requirements, to be eligible for this position, you must have at least one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-09 grade level in the Federal Service. Specialized experience for this position includes: Applying descriptive or inferential statistical methods to analyze data, identify trends or patterns, evaluate results, and develop findings, reports, or recommendations; Using programming, query, or scripting languages, such as Structured Query Language (SQL), R, Python, SAS, or equivalent tools, to extract, transform, analyze, or prepare data for analysis; Experience manipulating datasets in relational databases (e.g., Compliance Data Warehouse, Enterprise Data Platform); Applying statistical or data science techniques, such as forecasting, predictive modeling, machine learning, optimization, or exploratory data analysis, to evaluate data or support analytic findings; and Creating reports, dashboards, visualizations, written summaries, or presentations to communicate statistical or technical findings to technical or non-technical audiences.
OR
EDUCATION: You may substitute education for specialized experience as follows: A Ph.D. or equivalent doctoral degree as described in the basic requirements in mathematics, statistics, computer science, data science or field directly related to the position. The degree must be in a major field of study (at least at the baccalaureate level) that is appropriate for the position.
OR
Three (3) full academic years of progressively higher-level graduate education leading to a PH.D or equivalent doctoral degree in mathematics, statistics, computer science, data science or field directly related to the position. The degree must be in a major field of study (at least at the baccalaureate level) that is appropriate for the position.
OR
COMBINATION OF EDUCATION AND EXPERIENCE: You may qualify with an equivalent combination of qualifying experience and education.
SPECIALIZED EXPERIENCE GRADE 12: In addition to the basic requirements above, to be eligible for this position at the GS-12 level, you must have one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-11 grade level in the Federal service. Specialized experience for this position includes experience performing all the following:
  • Planning and carrying out data analysis assignments by applying descriptive or inferential statistical methods to analyze data from multiple sources, validate results, identify trends or patterns, and develop findings, reports, or recommendations.
  • Using programming, query, or scripting languages, such as Structured Query Language (SQL), R, Python, SAS, or equivalent tools, to extract, transform, validate, analyze, visualize, or document structured or unstructured data for data science projects.
  • Experience manipulating datasets in relational databases (e.g., Compliance Data Warehouse, Enterprise Data Platform).
  • Applying statistical or data science techniques, such as forecasting, predictive modeling, machine learning, optimization, prescriptive analysis, or exploratory data analysis, to evaluate data, models, programs, or operations and make projections or recommendations.
  • Creating and presenting reports, dashboards, visualizations, written summaries, or presentations that explain statistical or technical methods, findings, limitations, or recommendations to managers, stakeholders, customers, or project teams.

SPECIALIZED EXPERIENCE GRADE 13: In addition to the basic requirements above, to be eligible for this position at the GS-13 level, you must have one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-12 grade level in the Federal service. Specialized experience for this position includes experience performing all the following:
  • Independently planning and carrying out data science or statistical analysis projects by defining analytic questions, selecting data sources or methods, analyzing structured or unstructured data, validating results, and developing findings or recommendations.
  • Developing or applying statistical, machine learning, operations research, or other data science methods to evaluate programs, operations, compliance, or organizational performance, for example forecasting, predictive or prescriptive modeling, optimization, natural language processing or text analytics, graph or link analysis, or exploratory data analysis.
  • Using programming, query, scripting, or analytic tools, such as Structured Query Language (SQL), R, Python, SAS, or equivalent tools, to prepare, transform, document, analyze, and visualize data for data science projects.
  • Experience manipulating datasets in relational databases (e.g., Compliance Data Warehouse, Enterprise Data Platform).
  • Documenting analytic approaches, assumptions, limitations, validation results, success measures, or key performance indicators, and presenting technical findings or recommendations to managers, stakeholders, customers, or cross-functional teams.

AND
You must also meet the following requirements:
  • MINIMUM AGE REQUIREMENT: Minimum age for federal employment is 18 years old, or at least 16 years old and have:
    • Graduated from high school or been awarded a certificate equivalent to graduating from high school; or
    • Completed a formal vocational training program; or
    • Received a statement from school authorities agreeing with your preference for employment rather than continuing your education

For more information on qualifications please refer to OPM's Qualifications Standards.Education:A college or university degree generally must be from an accredited (or pre-accredited) college or university recognized by the U.S. Department of Education. For a list of schools which meet these criteria, please refer to Department of Education Accreditation page.
FOREIGN EDUCATION: Education completed in foreign colleges or universities may be used to meet the requirements. You must show proof the education credentials have been deemed to be at least equivalent to that gained in conventional U.S. education program. It is your responsibility to provide such evidence when applying. Click here (Section 3, Explanation of Terms) or here for Foreign Education Credentialing instructions.
We recommend choosing an evaluator from a member organization of one of the following national associations of credential evaluation services: National Association of Credential Evaluation Services (NACES) or Association of International Credentials Evaluators (AICE).Employment Type: OTHER

What U.S. Department Of The Treasury employees say

Pay

Hours and flexibility

Workplace

Get the full story on Breakroom

Apply