ZipRecruiter

Log In

1

Data Science Jobs in Riverside, CA (NOW HIRING)

Hireblazer

Senior Data Scientist

Irvine, CA · On-site

Collaborate effectively with internal clients to translate their needs into data science use cases. Provide ongoing tracking and monitoring of model performance and recommend improvements to methods ...

Mindlance

3D Data Scientist

Irvine, CA · On-site

The role involves leading the validation of 3D data science capabilities and collaborating across functions to develop new 3D digital endpoints for aesthetic applications. Responsibilities : • Lead ...

New

Kia America, Inc.

Data Scientist- Applied AI

Irvine, CA · On-site +1

This role focuses on applying data science and AI techniques to analyze text and other unstructured data, build models, and generate insights that support business decisions. The role contributes to ...

Kia America

Data Scientist- Applied AI

Irvine, CA · On-site

This role focuses on applying data science and AI techniques to analyze text and other unstructured data, build models, and generate insights that support business decisions. The role contributes to ...

Kia America

Data Scientist- Applied AI

Irvine, CA · On-site +1

This role focuses on applying data science and AI techniques to analyze text and other unstructured data, build models, and generate insights that support business decisions. The role contributes to ...

Corvel

Data Scientist II

Irvine, CA · On-site +1

$82K - $127K/yr

Translate business and operational needs into scalable data science solutions and modeling approaches * Perform feature engineering, data preparation, and exploratory analysis to support model ...

iHerb

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

Pricing Data Scientist

Irvine, CA

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

Corvel

Data Scientist II

Irvine, CA · On-site +1

Translate business and operational needs into scalable data science solutions and modeling approaches * Perform feature engineering, data preparation, and exploratory analysis to support model ...

Brillio

Senior Data Scientist - R01566194

Santa Ana, CA · On-site

$125K - $130K/yr

Experience Range: 5 - 8 years of experience in advanced data science roles Key Responsibilities: 1. Design and implement advanced statistical models and machine learning algorithms to solve complex ...

AbbVie

Data Science Program Lead I

Irvine, CA · On-site

$84K/yr

AbbVie Data Science is the best-in-class team within its cross-industry peer group and is responsible for bringing people, process, and technology together to generate business value from clinical ...

next page

Showing results 1-20

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 Jun 12, 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.

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.

Is 40 too late for data science?

Data science is a field open to individuals of all ages, and many professionals transition into it later in their careers. Success often depends on acquiring relevant skills such as programming, statistics, and machine learning, which can be learned through online courses, bootcamps, or degrees regardless of age.

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.

Is AI replacing data scientists?

AI is transforming the role of data scientists by automating routine tasks such as data cleaning and basic analysis, but it does not replace the need for skilled professionals to interpret complex data, develop models, and make strategic decisions. Data scientists with expertise in programming, statistical analysis, and machine learning remain essential for designing and deploying AI solutions effectively.

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 jobs are there in data science?

Data science offers a variety of roles including Data Scientist, Data Analyst, Machine Learning Engineer, Data Engineer, and Business Intelligence Analyst. These positions typically require skills in programming, statistics, and data visualization tools, and may involve working with large datasets, predictive modeling, and data-driven decision making.

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.

What jobs does a data scientist do?

A data scientist analyzes large datasets to extract insights, build predictive models, and support decision-making. They use programming languages like Python or R, employ statistical techniques, and often work with machine learning algorithms to solve complex problems across various industries.
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:
What are popular job titles related to Data Science jobs in Riverside, CA? 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 June 2026, with employment types broken down into 75% Full Time, and 25% Part Time. Highlights an 100% In-person job distribution, with an average salary of $128,049 per year, or $61.6 per hour.

Senior Data Scientist

Hireblazer

Irvine, CA • On-site

Full-time

Posted 19 days ago

Job description

Job Title: Sr. Data Scientist

Location: Irvine, CA (Hybrid - Onsite and Remote) or San Francisco Market St (Onsite) or Telecommute (Remote)

Contract Type: Contract to Hire

Project Overview:

The Sr. Data Scientist will join the Personalization Data Science and Machine Learning team to focus on solving recommendations, ranking, user condition predictions, and search problems. This KPI-driven team leverages Machine Learning (ML) to deliver personalized experiences. The role involves building end-to-end solutions, collaborating with data scientists and engineers, and ensuring engineering excellence with solid production releases. The team utilizes state-of-the-art machine learning and strives for low-latency solutions.

Top Responsibilities:

Apply advanced statistical and predictive modeling techniques to optimize healthcare and digital experiences.

Propose innovative solutions using data mining, statistical analysis, and machine learning.

Support business needs related to analytics, predictive modeling, and business intelligence.

Collaborate effectively with internal clients to translate their needs into data science use cases.

Provide ongoing tracking and monitoring of model performance and recommend improvements to methods and algorithms.

Required Qualifications:

Bachelor's Degree (Minimum Education Requirement).

Strong hands-on skills in Data Analytics and ML-Ops.

Ability to turn state-of-the-art research into production-level code.

Experience developing analytics with machine learning, deep learning, NLP, and/or other related modeling techniques.

Proficiency in Python, TensorFlow, PyTorch, and/or PySpark.

Ability to translate business needs and requirements into technical solutions.

Solid analytical and problem-solving skills.

Preferred Qualifications:

Master's or Ph.D. degree in Computer Science, Applied Mathematics, (Bio) Statistics, Applied Statistics, Economics, or similar quantitative fields.

Experience developing and deploying models related to recommender systems, NLP, and time series forecasting.

Experience developing algorithms for search engines (e.g., name entity recognition, intent classification, spell correction, auto-completion), cold-start recommendation, and semi-supervised learning (e.g., positive unlabeled learning).