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Data Analytics Jobs in Riverside, CA (NOW HIRING)

VSolvit

BUSINESS DATA ANALYST 2

Norco, CA · On-site

$88K - $120K/yr

Bachelor's degree in Data Analytics, Computer Science, Information Systems, Mathematics, Statistics, Business Analytics, or a related field. * 2 to 6 years of experience as a Data Analyst or in a ...

Fujifilm

Director Data AI & Analytics

Irvine, CA · Hybrid

The Director Data, AI and Analytics will own the strategy, platforms, operating model, and outcomes for Data, AI, and Analytics across three FUJIFILM lifesciences businesses. In highly regulated GxP ...

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All JobsData Analytics JobsData Analytics Jobs in Riverside, CA

Data Analytics information

See Riverside, CA salary details

$25

$57

$98

How much do data analytics jobs pay per hour?

As of Sep 14, 2026, the average hourly pay for data analytics in Riverside, CA is $57.12, according to ZipRecruiter salary data. Most workers in this role earn between $45.91 and $64.71 per hour, depending on experience, location, and employer.

What is data analytics?

Data analytics is the process of examining raw data to uncover trends, patterns, and insights that can inform decision-making. Professionals in this field use statistical techniques, programming, and data visualization tools to interpret complex data sets. Data analytics is applied in various industries, including business, healthcare, finance, and technology, to optimize operations, improve customer experiences, and drive strategic initiatives. The field often requires knowledge of tools like Excel, SQL, Python, and specialized analytics platforms.

How does a data analytics professional typically collaborate with other departments within an organization?

Data Analytics professionals frequently work alongside teams such as marketing, finance, operations, and product development to identify trends, solve business problems, and inform strategic decisions. Collaboration often involves gathering data requirements, interpreting findings, and presenting actionable insights in a clear and accessible manner. Effective communication and the ability to translate technical data into business terms are essential for ensuring recommendations are implemented and drive measurable impact. Regular cross-functional meetings and project-based teamwork are common, offering opportunities to learn from other disciplines and broaden one's organizational influence.

What are the key skills and qualifications needed to thrive as a data analytics professional, and why are they important?

To thrive as a Data Analytics professional, you need strong quantitative analysis skills, proficiency in statistics, and a relevant degree such as in mathematics, computer science, or a related field. Experience with technical tools like SQL, Python or R, data visualization platforms (e.g., Tableau, Power BI), and sometimes certifications like Google Data Analytics or Microsoft Certified: Data Analyst Associate are highly valuable. Critical thinking, problem-solving, and effective communication are essential soft skills for interpreting data and presenting findings to stakeholders. These skills and qualities are crucial for transforming raw data into actionable insights that drive business decision-making.

What is the difference between Data Analytics vs Data Analyst?

AspectData AnalyticsData Analyst
Role FocusAnalyzing large datasets to identify trends and insightsInterpreting data, creating reports, and supporting decision-making
Skills & CertificationsStatistical skills, data visualization, tools like SQL, Python, RData visualization, Excel, SQL, basic statistical knowledge
Work EnvironmentOften in data teams, tech companies, or consulting firmsBusiness units, marketing, finance, or operations teams
Common UsageRefers to the field or disciplineRefers to the job role or position

While both roles involve working with data, Data Analytics typically refers to the broader field or discipline focused on analyzing data to extract insights. A Data Analyst is a specific job role within that field, responsible for interpreting data, creating reports, and supporting business decisions.

Is a data analyst still a good career?

Data analysts remain in high demand across industries due to the increasing reliance on data-driven decision making. Strong skills in tools like Excel, SQL, and visualization software, along with certifications, can enhance job prospects and career growth in this field.

What jobs can a data analyst do?

A data analyst can work in roles such as business analyst, data scientist, data engineer, or reporting specialist. They analyze data to help organizations make informed decisions, often using tools like Excel, SQL, and visualization software, and may require knowledge of statistical methods and programming languages like Python or R.

What kind of jobs can you get with data analytics?

Data analytics skills can lead to roles such as data analyst, business analyst, data scientist, and data engineer. These jobs involve analyzing data to support decision-making, often requiring proficiency in tools like Excel, SQL, and Python, and may require relevant certifications or a strong understanding of statistical methods.

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

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

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

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

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

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

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

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

Data Analytics jobs near you
Infographic showing various Data Analytics job openings in Riverside, CA as of September 2026, with employment types broken down into 100% Full Time. Highlights an 50% In-person, 25% Hybrid, and 25% Remote job distribution, with an average salary of $118,800 per year, or $57.1 per hour.

Data Scientist - Business Analytics & ML

Irvine, CA • On-site

Kia America
Automobile Dealers • 10K+ employees
Learn more about Kia Americaexternal

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 26 days ago

Kia rating

6.4

Company rating: 6.4 out of 10

Based on 153 frontline employees who took The Breakroom Quiz

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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