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Data Science Jobs in Riverside, CA (NOW HIRING)

Pwc

AI & GenAI Data Scientist-Director

Irvine, CA · On-site

$155K - $410K/yr

Industry/Sector Not Applicable Specialism Data Science Management Level Director & Summary The Opportunity As an AI & GenAI Data Scientist-Director, you will leverage advanced technologies and ...

iHerb, LLC

Pricing Data Scientist

Irvine, CA · On-site +1

Strong applied quantitative background with demonstrated experience designing, building, and deploying Python-based data science models, including production workflows, to inform pricing, promotions ...

iHerb.com

Pricing Data Scientist

Irvine, CA · On-site +1

Strong applied quantitative background with demonstrated experience designing, building, and deploying Python-based data science models, including production workflows, to inform pricing, promotions ...

iHerb, LLC

Pricing Data Scientist

Irvine, CA · On-site +1

$198K/yr

Strong applied quantitative background with demonstrated experience designing, building, and deploying Python-based data science models, including production workflows, to inform pricing, promotions ...

omega solutions, Inc.

Sr. Data Scientist

Santa Ana, CA · On-site

Sr. Data Scientist Santa Ana, CA 6 months : What is the specific title of the position? Senior Data Scientist What Project/Projects will the candidate be working on while on assignment? 1) Field Team ...

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All JobsData Science JobsData Science Jobs in Riverside, CA

Data Science information

See Riverside, CA salary details

$39.1K

$128K

$205K

How much do data science jobs pay per year?

As of Aug 15, 2026, the average yearly pay for 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.

Is a data scientist in high demand?

Yes, data scientists are in high demand across many industries due to the increasing reliance on data-driven decision making. The role requires skills in programming, statistics, and machine learning, and job growth is expected to continue as organizations expand their data capabilities.

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

To thrive as a Data Scientist, you need a strong background in statistics, programming (often Python or R), and data analysis, usually supported by a degree in a quantitative field. Familiarity with machine learning libraries (like scikit-learn or TensorFlow), big data tools (such as Hadoop or Spark), and data visualization platforms is typically required. Critical thinking, problem-solving, and effective communication are vital soft skills for translating complex data insights into actionable business strategies. These skills and qualities are essential for extracting value from data, driving informed decisions, and effectively collaborating with multidisciplinary teams.

What are some common challenges faced by data scientists when working with real-world datasets?

Data scientists often encounter challenges such as missing or inconsistent data, unstructured formats, and noisy information in real-world datasets. Cleaning and preprocessing data to ensure its quality can be time-consuming but is critical for building accurate models. Additionally, data scientists may work closely with domain experts and other team members to better understand the data's context and ensure their analyses align with business objectives. Overcoming these challenges requires strong problem-solving skills and effective collaboration within cross-functional teams.

What is data science?

Data science is an interdisciplinary field that uses scientific methods, algorithms, and systems to extract insights and knowledge from structured and unstructured data. It combines skills from statistics, computer science, and domain expertise to analyze and interpret complex data sets. Data scientists work with large amounts of data to identify patterns, make predictions, and help organizations make data-driven decisions.

What is the difference between Data Science vs Data Analyst?

AspectData ScienceData Analyst
Required skillsStatistics, programming (Python, R), machine learningData visualization, SQL, basic statistics
Work environmentDeveloping models, predictive analytics, researchReporting, data cleaning, descriptive analysis
Tools usedPython, R, Jupyter, TensorFlowExcel, SQL, Tableau, Power BI
Industry usageTech, finance, healthcare, e-commerceRetail, marketing, finance, healthcare

Data Science and Data Analyst roles often overlap but differ mainly in scope. Data Scientists focus on building predictive models and advanced analytics, requiring programming and machine learning skills. Data Analysts primarily handle data cleaning, reporting, and visualization. Both roles are essential in data-driven industries, but Data Science is more technical and research-oriented, while Data Analysis emphasizes interpreting data for business insights.

What does a data scientist do?

As a Data Scientist, you are qualified to work in such diverse fields as research and development, politics, advertising and marketing, technology, healthcare, government, and higher education as well as multiple others. In general, your duties and responsibilities will be to compile and analyze relevant statistics and turn those numbers into algorithms that reveal insights that can be used by other researchers in their areas of study. Data Science can reveal things like consumer buying habits or the likelihood of success for a course of action. Other duties might vary, depending on your unique field of specialty. Related areas in which a Data Scientist might wish to focus include work as a Data Analyst, Machine Learning Engineer, and Project Manager.
More about Data Science jobs

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:

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

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

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

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

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

Data Science jobs near you
Infographic showing various Data Science job openings in Riverside, CA as of August 2026, with employment types broken down into 86% Full Time, and 14% Part Time. Highlights an 89% In-person, and 11% Remote job distribution, with an average salary of $128,049 per year, or $61.6 per hour.

Data Scientist - Business Analytics & ML

Kia America

Irvine, CA • On-site, Remote

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 6 days ago

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.

Kia America logo

About Kia America

Sourced by ZipRecruiter

Industry

Motor vehicle manufacturing

Company size

501 - 1,000 Employees

Headquarters location

Irvine, CA, US

Year founded

1994

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