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Chief Data Analytics Jobs in Riverside, CA (NOW HIRING)

Conexus

CIO

Irvine, CA · On-site

$350K/yr

CIO Position Summary: Seeking a customer-centric, business-minded technology leader to elevate how ... Applications, Data & Analytics: Oversee application development, integrations, and advanced ...

GHJ

Chief Financial Officer

Rancho Cucamonga, CA

$225K - $250K/yr

Oversee accounting, FP&A, treasury, and risk management functions * Ensure accurate financial ... If you would like more information about how your data is processed, please contact us.

GHJ

Chief Financial Officer

Rancho Cucamonga, CA · On-site

$225K - $250K/yr

Oversee accounting, FP&A, treasury, and risk management functions * Ensure accurate financial ... If you would like more information about how your data is processed, please contact us. apply for ...

GHJ

Chief Financial Officer

Rancho Cucamonga, CA · On-site

$225K - $250K/yr

Oversee accounting, FP&A, treasury, and risk management functions * Ensure accurate financial ... If you would like more information about how your data is processed, please contact us.

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Showing results 1-20

All JobsChief Data Analytics JobsChief Data Analytics Jobs in Riverside, CA

Chief Data Analytics information

See Riverside, CA salary details

$34.4K

$129.8K

$209.2K

How much do chief data analytics jobs pay per year?

As of Jul 10, 2026, the average yearly pay for chief data analytics in Riverside, CA is $129,792.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,000.00 and $152,300.00 per year, depending on experience, location, and employer.

How much does a chief data analyst make?

A chief data analyst typically earns between $80,000 and $150,000 annually, depending on experience, industry, and location. Senior roles may include bonuses and benefits, and proficiency in data tools like SQL and Python can influence salary levels.

What are the key skills and qualifications needed to thrive as a Chief Data Analytics, and why are they important?

To thrive as a Chief Data Analytics, you need advanced expertise in data science, statistical analysis, and business intelligence, often supported by a master's or doctoral degree in a quantitative field. Familiarity with analytics platforms (such as Tableau, Power BI), big data tools (like Hadoop, Spark), and programming languages (Python, R), as well as certifications in data analytics or management, are typically required. Strategic thinking, strong leadership, and effective communication skills are essential to bridge the gap between technical teams and business stakeholders. These competencies are crucial for driving data-driven decision-making, aligning analytics initiatives with organizational goals, and delivering measurable business value.

How does a Chief Data Analytics professional typically collaborate with other departments to drive data-driven decision making?

As a Chief Data Analytics professional, you'll work closely with leaders from departments such as marketing, finance, operations, and IT to identify key business challenges and opportunities where data can provide actionable insights. Regular cross-functional meetings, workshops, and data strategy sessions are common to ensure alignment on goals and data priorities. You'll also guide teams on best practices for data collection, analysis, and interpretation, fostering a culture of data-driven decision making throughout the organization. Building strong relationships and maintaining clear communication with stakeholders is essential to drive successful analytics initiatives and support organizational growth.

What is the highest paying job in data analytics?

The highest paying roles in data analytics are often senior positions such as Chief Data Officer or Data Science Director, which require extensive experience, advanced skills in machine learning and big data tools, and often involve strategic decision-making responsibilities. These roles can offer salaries exceeding $150,000 annually, depending on the industry and location.

What does a Chief Data Analytics Officer do?

A Chief Data Analytics Officer (CDAO) is responsible for overseeing an organization's data strategy, analytics initiatives, and data-driven decision making. They lead teams that collect, analyze, and interpret data to support business goals and drive innovation. The CDAO ensures that data governance, quality, and privacy standards are met, while also promoting a data-centric culture across the company. Their work helps organizations leverage data assets to gain competitive advantage and improve performance.

What is a CDO salary?

A Chief Data Officer (CDO) salary varies based on experience, industry, and location but typically ranges from $150,000 to over $300,000 annually. CDOs often have strong backgrounds in data management, analytics, and leadership, and may receive bonuses or stock options as part of their compensation package.

What is the difference between Chief Data Analytics vs Data Analyst?

AspectChief Data AnalyticsData Analyst
CredentialsAdvanced degrees (Master's, PhD), certifications in data management and analyticsBachelor's or Master's in Data Science, Statistics, or related fields
Work EnvironmentStrategic leadership, overseeing analytics teams, executive collaborationData analysis, reporting, and visualization tasks, often under supervision
Employer & Industry UsageUsed in large organizations, tech firms, finance, healthcareCommon across various industries, including retail, marketing, finance

Chief Data Analytics focuses on strategic leadership, managing analytics teams, and aligning data initiatives with business goals. Data Analysts perform hands-on data analysis, reporting, and visualization. Both roles require strong analytical skills, but the Chief Data Analytics role involves higher-level decision-making and leadership responsibilities.

What does a chief data analyst do?

A chief data analyst is responsible for analyzing complex data sets to identify trends and support strategic decision-making within an organization. They develop data models, create reports, and use tools like SQL and data visualization software to communicate insights to stakeholders. Strong analytical skills and knowledge of data management are essential for this role.
What are popular job titles related to Chief Data Analytics jobs in Riverside, CA? For Chief Data Analytics jobs in Riverside, CA, the most frequently searched job titles are:
What job categories do people searching Chief Data Analytics jobs in Riverside, CA look for? The top searched job categories for Chief Data Analytics jobs in Riverside, CA are:
What cities near Riverside, CA are hiring for Chief Data Analytics jobs? Cities near Riverside, CA with the most Chief Data Analytics job openings:
Chief Data Analytics jobs near you
Sr. Director, Enterprise Data, Analytics, AI & Automation

Sr. Director, Enterprise Data, Analytics, AI & Automation

Mazda Motor Corporation

Irvine, CA • On-site, Remote

$111K - $145K/yr

Full-time

Posted 10 days ago

Job description

Job Description
The Senior Director of Enterprise Data, Analytics, AI and automation is responsible for defining and executing the enterprise strategy for data, analytics, artificial intelligence, and intelligent automation. This leader will build the foundational capabilities, governance, platforms and operating models required to transform the data into a strategic asset, enable AI-powered business outcomes across the organization.
Reporting to the Chief Information Officer, the role will partner closely with business leaders, technology teams, and external partners to modernize decision-making, automate business processes, accelerate innovation, and deliver measurable business value through data-driven intelligence.
The successful candidate will lead the organization's Data & AI transformation agenda, ensuring that analytics, automation, machine learning, generative AI, and agentic AI capabilities are implemented responsibly, securely, and at scale.
Major Responsibilities
  • (20%) Enterprise Data/AI Strategy and Portfolio Management
    • Define and execute the enterprise Data, Analytics, AI, and Automation strategy aligned with business priorities and long-term corporate objectives.
    • Develop and maintain a multi-year roadmap for data modernization, AI adoption, advanced analytics, and intelligent automation.
    • Establish enterprise investment priorities, performance metrics, and value realization frameworks for Data & AI initiatives.
    • Advise executive leadership on emerging technologies, AI trends, opportunities, and risks to enable informed strategic decisions and responsible innovation.
    • Prioritize the enterprise Data & AI portfolio in partnership with the business based on strategic alignment, business value, and organizational readiness.

  • (20%) Enterprise Data Platform Architecture, Data Operations, and Governance
    • Lead the strategy, architecture, development, and operation of the enterprise data platform, including the Enterprise Data Warehouse, Azure Data Lake, Databricks Lakehouse, integration services, and enterprise reporting environments.
    • Establish enterprise data governance, data quality, metadata management, master data management, and information protection capabilities.
    • Oversee enterprise data architecture, pipelines, integration patterns, and platform operations, ensuring reliability, scalability, security, compliance, and performance.
    • Deliver trusted, accessible, and reusable enterprise data products that accelerate analytics delivery and improve business decision-making.
    • Manage enterprise analytics platforms and visualization technologies, including Power BI and cloud-based analytics services.
    • Drive enterprise data democratization through secure, governed self-service access to trusted data and business insights.

  • (20%) Advanced Analytics, AI & Intelligent Decision Support
    • Develop enterprise analytics capabilities that improve decision-making, customer outcomes, operational performance, and business growth.
    • Expand enterprise analytics and AI capabilities-including predictive analytics, machine learning, real-time intelligence, and self-service reporting-to improve decision-making and business outcomes.
    • Lead enterprise AI strategy, initiatives delivery across machine learning, generative AI, agentic AI, copilots, and intelligent digital capabilities, enabling new ways of working and to create business value.
    • Partner with business leaders to identify, prioritize, and scale high-value AI use cases across customer, dealer, employee, and enterprise operations.
    • Establish Responsible AI governance, policies, model lifecycle management, and AI risk management practices.
    • Measure adoption rate, business value, and operational impact of analytics and AI solutions through defined KPIs and value realization metrics.

  • (20%) Intelligent Automation, Enterprise AI Enablement and Adoption
    • Execute the enterprise strategy for intelligent automation and AI-enabled business transformation across business and technology functions.
    • Drive adoption of intelligent automation and AI capabilities, including RPA and AI-powered solutions, to improve productivity, efficiency, and employee experience.
    • Drive adoption of workflow automation and robotic process automation (RPA). Lead enterprise deployment, governance, and adoption of AI platforms including Microsoft Copilot, Claude, and future enterprise AI capabilities.
    • Co-own the enterprise AI Workforce Strategy in partnership with Human Resources (HR) , establishing the operating model, governance framework, workforce readiness assessments, role impact analysis, capability-building programs, employee communications and change management required to scale Data/AI adoption responsibility across the enterprise.
    • Partner with Legal, Security, Risk, and IT to ensure the secure, ethical and compliant deployment and lifecycle management of AI technologies; serve as the technology co-owner alongside HR for all enterprise AI adoption, people readiness and organizational change programs.
    • Continuously evaluate emerging AI technologies, market trends, and vendor capabilities, translating innovation into scalable business solutions that create competitive advantage.
    • Establish shared metrics and governance with HR to track AI adoption rates, workforce capability growth, employee experience impact, and value realization across all AI enablement programs.

  • (20%) Organizational Leadership & Operational Excellence
    • Sets strategic direction across multiple departments and broad functions, aligning team priorities with enterprise objectives to drive cohesive execution.
    • Build, lead, and develop a high-performing organization of data architects, engineers, analysts, data scientists, AI engineers, automation specialists, product owners, and technical leaders.
    • Lead relationships with strategic data platform vendors, 3rd party data providers, and partners, including contracts, licensing, and technical delivery.
    • Establish operating models, delivery frameworks, engineering standards, product management disciplines, and talent strategies that enable enterprise scale.
    • Foster a culture of innovation, operational excellence, collaboration, continuous learning, data literacy, AI literacy, and measurable business outcomes.
    • Manage the Data & AI investment portfolio, including budgets, resource planning, sourcing strategies, strategic vendor partnerships, vendor performance, and financial stewardship.
    • Champion cross-functional partnerships that accelerate enterprise transformation and maximize business value.

  • Perform other duties as assigned
  • Comply with all policies and standards
  • The preceding functions have been provided as examples of the types of work performed by employees assigned to this job classification. Management reserves the right to add, modify, change or rescind the work assignments of different positions and to make reasonable accommodations so that qualified employees can perform the essential functions of the job

Work Experience
  • 10+ years progressive leadership experience in enterprise Data, Analytics, AI, Automation, or Digital Transformation, with accountability for enterprise strategy, delivery, and business outcomes required
  • 7+ years experience leading enterprise data platforms, cloud data architectures, analytics engineering, or data management organizations in a complex, matrixed enterprise required
  • 5+ years experience leading enterprise AI, machine learning, advanced analytics, or intelligent automation initiatives, including operating model design, governance, and enterprise adoption required
  • 5+ years experience with people leadership, organizational development, financial management, and strategic vendor management, including oversight of consulting partners, managed services, and technology providers required
  • Demonstrated success developing and executing multi-year technology roadmaps, investment strategies, and enterprise transformation programs preferred
  • Experience establishing enterprise data governance, AI governance, information management, and regulatory compliance programs preferred
  • Experience leading modern cloud data platforms and analytics ecosystems (e.g., Azure, Databricks, Microsoft Fabric, AWS, or Google Cloud) preferred
  • Experience leading enterprise ERP, CRM, and business intelligence ecosystems to support enterprise reporting, analytics, and operational decision-making preferred
  • Experience working within global or multinational organizations; experience in a Japanese-affiliated organization preferred
  • Automotive, manufacturing, retail, or other complex multi-channel enterprise experience preferred

Education
  • Bachelor of Science (BS) Computer and Information Science or related discipline is Required
  • Master of Science (MS) Computer and Information Science Preferred
  • Master of Business Administration (MBA) Preferred

Licenses and Certifications
  • Microsoft Certified: Azure Data Fundamentals - Microsoft Corporation Preferred Upon Hire
  • AWS Certified Data Analytics - Specialty - Scrum Alliance Preferred Upon Hire
  • Databricks Certified Data Engineer Associate - Databricks Preferred Upon Hire
  • Google Cloud Professional Cloud Architect - Google Cloud Preferred Upon Hire
  • Certified Data Management Professional (CDMP) - Data Management Association International (DAMA) Preferred Upon Hire
  • Agile Certified Practitioner (PMI-ACP) - Project Management Institute (PMI) Preferred Upon Hire
  • Project Management Professional (PMP) - Project Management Institute (PMI) Preferred Upon Hire

Knowledge, Skills, Abilities
  • Deep expertise in enterprise data governance, data quality management, metadata management, and modern data architecture (Advanced-Authority)
  • Demonstrated ability to develop, operationalize, and scale enterprise AI enablement programs, including use case identification, governance, change management, and cross-functional adoption (Advanced-Authority)
  • Strong understanding of advanced analytics, statistical modeling, machine learning, and AI technologies, with the ability to lead highly technical teams and guide architectural and technology decisions (Advanced-Authority)
  • Working knowledge of programming and query languages commonly used in modern data environments (e.g., Python, SQL, R; Java and C++) (Advanced-Authority)
  • Comprehensive knowledge of data privacy, cybersecurity, regulatory compliance, and emerging AI governance and Responsible AI frameworks (Advanced-Authority)
  • Proven experience managing strategic technology vendors, negotiating complex contracts, and overseeing large-scale data and AI platform partnerships (Advanced-Authority)
  • Executive presence with exceptional written and verbal communication skills; able to translate complex technical concepts into clear business insights for executive leadership and board-level audiences (Advanced-Authority)
  • Demonstrated ability to lead and influence across a complex, matrixed organization while building trusted relationships with business and technology stakeholders (Advanced-Authority)
  • Strong portfolio, program, and project management capabilities, with the ability to prioritize competing initiatives and deliver measurable business outcomes in a fast-paced environment (Advanced-Authority)
  • Collaborative and inclusive leadership style with the ability to coach teams, influence peers, and build alignment across executive and cross-functional stakeholders (Advanced-Authority)
  • Proficiency with Microsoft 365, Power BI, Copilot, and other enterprise AI productivity and collaboration platforms (Advanced-Authority)
  • Consistently demonstrates MNAO's Leadership Competencies and Pride Point behaviors while fostering a culture of innovation, accountability, collaboration, and continuous improvement (Advanced-Authority)

Physical Demands
  • Stationary Position/Seated: Constantly
  • Communicate/Talking: Constantly
  • Communicate/Hearing: Constantly
  • Seeing/Observing: Constantly

Travel Requirements
  • 10% Flying Domestic: Essential

#LI-Remote
We support Remote work in the following states:
Alabama, Arizona, California, Colorado, Connecticut, Delaware, District of Columbia, Florida, Georgia, Hawaii, Idaho, Illinois, Indiana, Kansas, Kentucky, Louisiana, Maryland, Massachusetts, Michigan, Minnesota, Missouri, Nevada, New Hampshire, New Jersey, New Mexico, New York, North Carolina, Ohio, Oklahoma, Oregon, Pennsylvania, Rhode Island, South Carolina, Tennessee, Texas, Utah, Virginia, Washington, Wisconsin
Pay Range
$228,600.00 - $348,600.00
Salary to be determined by education, experience, knowledge, skills and abilities of the applicant, internal equity, and alignment with market data.
Learn more about MNAO's comprehensive benefits package here

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