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Data Analysis Assistant Jobs in Riverside, CA (NOW HIRING)

Artemis Professionals, LLC

Be Seen First

Staff Accountant

Jurupa Valley, CA · On-site

$70K - $80K/yr

... analysis, and account reconciliations. * Assist with the monthly, quarterly, and year-end close ... Proficiency with Microsoft Excel, including formulas, sorting, filtering, and basic data analysis.

New

K-1 Speed Inc

Senior Accountant

Irvine, CA · On-site

$95K - $105K/yr

Prepare audit requests for external audit * Assist with sales and use tax monthly filings * Participate in special projects, data analysis, and reporting as required by management What we're looking ...

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All JobsData Analysis JobsData Analysis Assistant JobsData Analysis Assistant Jobs in Riverside, CA

Data Analysis Assistant information

See Riverside, CA salary details

$11

$19

$28

How much do data analysis assistant jobs pay per hour?

As of Sep 4, 2026, the average hourly pay for data analysis assistant in Riverside, CA is $19.88, according to ZipRecruiter salary data. Most workers in this role earn between $16.78 and $22.31 per hour, depending on experience, location, and employer.

What does a data analysis assistant do?

A Data Analysis Assistant supports data analysts and data scientists by collecting, cleaning, organizing, and preparing data for analysis. They help ensure the accuracy and integrity of datasets, create basic reports or visualizations, and may assist with statistical analysis or data entry tasks. Their work allows the analysis team to focus on more complex data interpretation and decision-making, making the assistant an essential part of the data workflow.

What are the key skills and qualifications needed to thrive as a data analysis assistant?

To thrive as a Data Analysis Assistant, you need a solid background in statistics, data interpretation, and proficiency with spreadsheets, often supported by a relevant degree or coursework. Familiarity with data analysis tools such as Microsoft Excel, SQL, and basic knowledge of programming languages like Python or R is commonly required. Attention to detail, critical thinking, and strong communication skills help you effectively process data and present findings. These competencies are crucial for ensuring accurate data handling, supporting sound business decisions, and enabling effective teamwork.

What are some common challenges faced by data analysis assistants when supporting multiple projects simultaneously?

Data Analysis Assistants often juggle several projects at once, which can make prioritizing tasks and managing time a challenge. Balancing the differing data requirements, deadlines, and communication with multiple team members requires strong organizational skills and adaptability. It's important to maintain clear documentation, proactively clarify expectations with project leads, and regularly update stakeholders on progress. Effective use of tools for tracking assignments and deadlines can help ensure accuracy and timely delivery of analyses.

What is the difference between Data Analysis Assistant vs Data Analyst?

AspectData Analysis AssistantData Analyst
Required CredentialsAssociate's degree or relevant certificationsBachelor's degree or higher in related fields
Work EnvironmentSupportive, entry-level roles in offices or teamsIndependent or team-based analysis in various industries
Employer & Industry UsageEntry-level support roles across sectorsData-driven decision-making roles in multiple industries
Common Search & ComparisonOften compared for entry-level data support rolesMore advanced, analytical positions

The Data Analysis Assistant typically performs entry-level support tasks, assisting with data collection and basic analysis, often requiring an associate's degree or certifications. In contrast, Data Analysts handle more complex data interpretation, reporting, and strategic insights, usually holding a bachelor's degree or higher. While both roles work in similar environments, the Data Analyst role involves greater responsibility and independence.

What are the most commonly searched types of Data Analysis jobs in Riverside, CA?

The most popular types of Data Analysis jobs in Riverside, CA are:

What are popular job titles related to Data Analysis Assistant jobs in Riverside, CA?

For Data Analysis Assistant jobs in Riverside, CA, the most frequently searched job titles are:

What job categories do people searching Data Analysis Assistant jobs in Riverside, CA look for?

The top searched job categories for Data Analysis Assistant jobs in Riverside, CA are:

What cities near Riverside, CA are hiring for Data Analysis Assistant jobs?

Cities near Riverside, CA with the most Data Analysis Assistant job openings:

Data Analysis Assistant jobs near you
Infographic showing various Data Analysis Assistant job openings in Riverside, CA as of August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 15% Part Time, and 3% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $41,344 per year, or $19.9 per hour.

Data Scientist - Business Analytics & ML

Kia America

Irvine, CA • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 16 days ago

Kia rating

6.3

Company rating: 6.3 out of 10

Based on 152 frontline employees who took The Breakroom Quiz

41st of 45 rated automakers

Job description

At Kia, we're creating award-winning products and redefining what value means in the automotive industry. It takes a special group of individuals to do what we do, and we do it together. Our culture is fast-paced, collaborative, and innovative. Our people thrive on thinking differently and challenging the status quo. We are creating something special here, a culture of learning and opportunity, where you can help Kia achieve big things and most importantly, feel passionate and connected to your work every day.
Kia provides team members with competitive benefits including premium paid medical, dental and vision coverage for you and your dependents, 401(k) plan matching of 100% up to 6% of the salary deferral, and paid time off. Kia also offers company lease and purchase programs, company-wide holiday shutdown, paid volunteer hours, and premium lifestyle amenities at our corporate campus in Irvine, California.
Status
Exempt
General Summary
The Data Scientist plays an important role in executing data analysis for Kia North America's regional subsidiaries (KUS/KCA/KaGA/KMX). Kia's Big Data Analysis team leverages vast and diverse datasets to drive business improvements and insights. The role requires expertise in statistics, machine learning, and computer science to utilize high-performance compute clusters and perform reproducible analyses at scale. This position supports the application of data, analytics, automation, and responsible AI to advance Kia's business operations.
This role focuses on using data and machine learning to answer complex business questions, build analytical and predictive models, and translate results into clear insights and recommendations for stakeholders. The role goes beyond reporting by framing problems, designing analyses, and influencing decisions.
Essential Duties and Responsibilities
1st Priority - 30%
Business Problem Framing, Data Wrangling & Analysis
  • Assess the accuracy of new data sources
  • Understand business processes and decision frameworks, and translate them into data-driven metrics and KPIs.
  • Preprocess structured and unstructured data
  • Analyze large amounts of data to discover trends and patterns
  • Build prediction and classification models
  • Coordinate with different functional teams for feature engineering
  • Partner with business stakeholders to frame problems, define success metrics, and translate business questions into analytical approaches

2nd Priority - 30%
Insight Generation, Visualization & Model Improvement
  • Test and continuously improve the accuracy of statistical and machine learning models
  • Present insights in a way that clearly ties analysis to business decisions and actions
  • Frame and communicate complex analyses in business-relevant terms that non-technical stakeholders can understand and act on
  • Continuously monitor and validate production analysis results

3rd Priority - 20%
Collaborate with IT Team to deploy analysis results
  • Build REST APIs for data and analysis result consumption
  • Assist the IT system developers to deploy analysis as a service

4th Priority - 20%
Clear documentation, source code management, and reproducible analysis
  • Use git within GitLab
  • Create virtual environments to isolate project dependencies and requirements
  • Track model performance and hyperparameter configurations
  • Track data versioning

This list of essential responsibilities and duties is not exhaustive and may be supplemented and changed as necessary by management.
Qualifications/Education
Education:
  • Bachelor's degree in a quantitative field required (e.g., Data Science, Statistics, Computer Science, Engineering, Economics, Mathematics, Business Analytics, or related field)
  • Master's degree in a quantitative field preferred

Job Requirement
  • 3+ years of experience in data science preferred.
  • Strong data analysis and statistical foundations required.
  • Proficiency in Python and SQL required.
  • Familiarity with applied machine learning concepts required.
  • Strong business acumen and ability to coordinate between technical teams and non-technical business stakeholders.
  • Experience querying databases and using programming languages such as Python and SQL
  • Experience using statistics and machine learning algorithms
  • Experience with big data processing frameworks such as Spark (e.g., PySpark); experience with Hadoop ecosystem or cloud platforms (e.g., Databricks, AWS) preferred
  • Experience publishing results to stakeholders through dashboards (e.g. Power BI, MicroStrategy, Tableau)

Specialized Skills and Knowledge Required
  • Proficiency in Python and SQL
  • Knowledge of a variety of machine learning techniques, deep learning a plus
  • Knowledge of advanced statistical techniques
  • Experience with common Python libraries for data analysis such as Pandas and NumPy
  • Experience with visualization libraries such as Matplotlib, Seaborn, Plotly, Bokeh and plotnine
  • Experience developing and evaluating statistical and machine learning models using libraries such as statsmodels and scikit-learn
  • Experience with big data processing tools such as Spark (e.g., PySpark); experience with Hadoop ecosystem or cloud platforms preferred
  • Experience with deep learning frameworks such as PyTorch and TensorFlow preferred
  • Strong data-driven problem-solving skills
  • Excellent written and verbal communication skills to coordinate across teams

Competencies
  • Care for People
  • Chase Excellence Every Day
  • Dare to Push Boundaries
  • Empower People to Act
  • Move Further Together

Pay Range
$89,936 - $121,409
Pay will be based on several variables that are unique to each candidate, including but not limited to, job-related skills, experience, relevant education or training, etc.
Equal Employment Opportunities
KUS provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, ancestry, national origin, sex, including pregnancy and childbirth and related medical conditions, gender, gender identity, gender expression, age, legally protected physical disability or mental disability, legally protected medical condition, marital status, sexual orientation, family care or medical leave status, protected veteran or military status, genetic information or any other characteristic protected by applicable law. KUS complies with applicable law governing non-discrimination in employment in every location in which KUS has offices. The KUS EEO policy applies to all areas of employment, including recruitment, hiring, training, promotion, compensation, benefits, discipline, termination and all other privileges, terms and conditions of employment.
Disclaimer: The above information on this job description has been designed to indicate the general nature and level of work performed by employees within this classification and for this position. It is not designed to contain or be interpreted as a comprehensive inventory of all duties, responsibilities, and qualifications required of employees assigned to this job.

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