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Data Science Jobs in Riverside, CA (NOW HIRING)

DIRECTOR, DATA SCIENCE & INSIGHTS REPORTS TO: CHIEF DIGITAL OFFICER STATUS: EXEMPT Summary Boot Barn is where community comes first. We thrive on togetherness, collaboration, and belonging. We build ...

DIRECTOR, DATA SCIENCE & INSIGHTS REPORTS TO: CHIEF DIGITAL OFFICER STATUS: EXEMPT Summary Boot Barn is where community comes first. We thrive on togetherness, collaboration, and belonging. We build ...

Data Scientist

Irvine, CA · On-site

$100K - $130K/yr

DIRECTOR OF DATA SCIENCE STATUS: EXEMPT Summary Boot Barn is where community comes first. We thrive on togetherness, collaboration, and belonging. We build each other up, listen intently, and ...

Data Scientist

Irvine, CA

$100K - $130K/yr

DIRECTOR OF DATA SCIENCE STATUS: EXEMPT Summary Boot Barn is where community comes first. We thrive on togetherness, collaboration, and belonging. We build each other up, listen intently, and ...

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 ...

... 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 ...

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Data Science information

See Riverside, CA salary details

$39.1K

$128K

$205K

How much do data science jobs pay per year?

As of Jul 25, 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 data science a good career?

Data science is a growing field with high demand for professionals skilled in statistics, programming, and data analysis tools like Python and R. It offers competitive salaries, diverse industry applications, and opportunities for advancement, making it a strong career choice for those with relevant skills and education.

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.

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 jobs can a Data Scientist do?

A Data Scientist can work in roles such as data analyst, machine learning engineer, data engineer, or business intelligence analyst. These roles involve analyzing large datasets, developing predictive models, and using tools like Python, R, and SQL to support decision-making across various industries.

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 work do you do as a Data Scientist?

A Data Scientist analyzes large datasets to extract insights, build predictive models, and inform business decisions. They use programming languages like Python or R, and tools such as SQL and machine learning frameworks, often working in collaborative environments with data engineers and analysts.

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 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:
Infographic showing various Data Science job openings in Riverside, CA as of July 2026, with employment types broken down into 73% Full Time, 18% Part Time, and 9% Contract. Highlights an 100% In-person job distribution, with an average salary of $128,049 per year, or $61.6 per hour.
Manager, Data Science

$154K/yr

Full-time

Medical, Dental, Vision, Life, Retirement

Posted 13 days ago


Job description

What you can expect! 

Find joy in serving others with IEHP! We welcome you to join us in “healing and inspiring the human spirit” and to pivot from a “job” opportunity to an authentic experience!

 

The Manager, Data Science leads a team of data scientists, ML engineers, and AI specialists. This role requires a strong balance of technical expertise in advanced machine learning (including Generative AI), leadership experience, health care domain knowledge preferably in the managed care space, and the ability to align AI-driven solutions with business strategy. The Manager, Data Science enables the development of production-grade ML models, building GenAI applications (LLMs, RAG pipelines, prompt engineering, finetuning, multimodal models), and drives measurable business outcomes.

 

Commitment to Quality: The IEHP Team is committed to incorporate IEHP’s Quality Program goals including, but not limited to, HEDIS, CAHPS, and NCQA Accreditation.


Perks

IEHP is not only committed to healing and inspiring the human spirit of our Members, but we also aim to match our team members with the same energy by providing prime benefits and more.

  • Competitive salary
  • State of the art fitness center on-site
  • Medical Insurance with Dental and Vision
  • Life, short-term, and long-term disability options
  • Career advancement opportunities and professional development
  • Wellness programs that promote a healthy work-life balance
  • Flexible Spending Account – Health Care/Childcare
  • CalPERS retirement
  • 457(b) option with a contribution match
  • Paid life insurance for employees
  • Pet care insurance

  1. Leadership & Strategy
    • Lead and mentor a team of data scientists, ML engineers, and AI specialists.
    • Define and execute the roadmap for AI/ML and Generative AI initiatives across the enterprise.
    • Partner with business and technology stakeholders to identify AI use cases that create measurable value.
    • Advocate for responsible AI practices, ensuring solutions are ethical, explainable, secure, and compliant.
  2. Technical & Delivery
    • Oversee development of advanced ML models and AI systems (predictive, prescriptive, and generative).
    • Design and implement GenAI solutions, including LLM fine-tuning, embeddings, retrieval-augmented generation (RAG), and prompt optimization.
    • Drive end-to-end MLOps practices: model training, evaluation, deployment, monitoring, and lifecycle management.
    • Ensure scalability and performance of AI solutions within enterprise data platforms.
    • Collaborate with data engineering to optimize data pipelines for AI workloads.
  3. Innovation & Research
    • Stay at the forefront of GenAI, multimodal AI, and emerging ML techniques to evaluate their
      relevance and application.
    • Foster a culture of experimentation, rapid prototyping, and “fail-fast and pivot” approaches.
  4. Hire, train, and manage support staff, while monitoring and evaluating outcomes. Conduct performance reviews of each team Member within IEHP guidelines.
  5. Perform any other duties as required to ensure Health Plan operations and department business needs are successful.

Education & Requirement

Required:

  • At least ten (10) years of experience, which should include a minimum of seven (7) years of experience in data science & ML and at least five (5) years in a leadership/managerial role
  • Proven track record in leading AI/ML projects from conception to production
  • Experience with cloud AI platforms (Azure ML, GCP Vertex AI) and/or on-prem MLOps setups
  • Direct experience in Managed Care and Healthcare analytics, including claims data, care management, utilization, risk adjustment, member engagement, or related areas
  • Exposure to multimodal AI (text, image, audio, video) applications
  • Experience with Kubernetes, KServe, Ray, or MLflow for scaling AI workloads
  • Bachelor's Degree in Mathematics, Statistics, Computer Science, or related field from an accredited institution
    • Master's Degree in Mathematics, Statistics, Computer Science, or related field from an accredited institution preferred

Key Qualifications

  • Familiarity with basic principles of distributed computing and/or distributed databases
  • Knowledge of one or more business/functional areas. Working knowledge of diagnosis and procedure coding, medical terminology, knowledge of managed care, claims payment processes, and insurance terminology required
  • Familiarity with data governance, model interpretability, bias mitigation, and AI ethics
  • Strong analysis and critical thinking skills. Excellent communication and interpersonal skills
  • Strong programming skills in Python, PyTorch/TensorFlow, LangChain, Hugging Face, or equivalent framework
  • Ability to manipulate large datasets and using database and general-purpose programming language (R, Python, JavaScript, or other big data frameworks, Java, SQL)
  • Demonstrable ability to quickly understand new concepts all the way down to the theorems, and to come out with original solutions to mathematical issues
  • Ability to multi-task while maintaining careful attention to detail. Ability to handle multiple projects, data input, and strong problem-solving capability. Independent self-starter who is driven to success, takes great pride in accomplishments and works with a sense of urgency to meet deadlines and address competing priorities
  • Expertise in Generative AI (LLMs, transformers, embeddings, vector databases, RAG, fine-tuning, and prompt engineering). Strong business acumen and ability to translate technical solutions into executive-level impact stories.

Start your journey towards a thriving future with IEHP and apply TODAY!


This position is on a hybrid work schedule. (Monday & Friday - remote, Tuesday – Thursday onsite in Rancho Cucamonga, CA.)

Willingness to be on call occasionally to attend to technical issues outside of normal business hours


USD $154,128.00 - USD $204,214.40 /Yr.