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Executive Predictive Analytics Jobs in California

Alter Management

Account Executive

Dana Point, CA · On-site

$90 - $120/hr

Account Executive Location: Corporate Office - Dana Point, CA Shift: 8:30am-5pm - Monday-Friday ... Care Predictor is the premier behavioral health predictive analytics-based, workforce development ...

Cetera

Marketing Analytics Manager

San Diego, CA

Build forecasting models, predictive analytics, and actionable segmentation to support marketing ... Ability to translate complex data into clear, concise, executive-ready insights, dashboards ...

New

Cetera

Marketing Analytics Manager

San Diego, CA · On-site

Build forecasting models, predictive analytics, and actionable segmentation to support marketing ... Ability to translate complex data into clear, concise, executive-ready insights, dashboards ...

New

ALTER MANAGEMENT

Account Executive

Dana Point, CA · On-site

$90/hr

Account Executive Location: Corporate Office - Dana Point, CA Shift: 8:30am-5pm - Monday-Friday ... Care Predictor is the premier behavioral health predictive analytics-based, workforce development ...

Alter Management LLC

Account Executive

Dana Point, CA · On-site

$90 - $120/hr

Care Predictor is the premier behavioral health predictive analytics-based, workforce development ... Executive)Develop business cases demonstrating ROI, efficiency gains, and improved patient ...

Apple

Senior Data Analyst - OS Stability

San Diego, CA

$142K - $263K/yr

... learning, predictive analytics, or automation tools Experience with MCP Servers, AI Agents ... to executive leadership and managing stakeholder relationships Minimum Qualifications BS in ...

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Executive Predictive Analytics information

What is an executive predictive analytics?

Executive Predictive Analytics refers to the use of advanced data analysis techniques and machine learning models by organizational leaders to forecast future business outcomes and inform strategic decisions. Executives use predictive analytics to anticipate market trends, identify risks and opportunities, and optimize resource allocation. This role requires a combination of business acumen, data science knowledge, and the ability to translate complex data into actionable insights for high-level decision-making.

How does an executive predictive analytics professional typically collaborate with other departments to drive business outcomes?

An Executive Predictive Analytics professional often works closely with teams across marketing, finance, operations, and IT to align advanced analytics initiatives with broader business goals. They translate complex data insights into actionable strategies, facilitating data-driven decision-making at the executive level. Regular cross-functional meetings and workshops are common to ensure that predictive models are integrated into business processes and that stakeholders understand their impact. Collaboration is key, as these executives must communicate technical findings in an accessible way to influence strategic planning and organizational change.

What are the key skills and qualifications needed to thrive as an executive in predictive analytics, and why are they important?

To thrive as an Executive in Predictive Analytics, you need advanced expertise in statistical analysis, data modeling, and business strategy, usually supported by a degree in data science, statistics, or a related field. Familiarity with analytics platforms such as SAS, R, Python, and big data tools, as well as certifications like Certified Analytics Professional (CAP), is highly beneficial. Exceptional leadership, communication, and strategic decision-making abilities set standout executives apart in this field. These skills enable leaders to drive data-informed organizational growth, align analytics initiatives with business objectives, and foster innovation across teams.

What is the difference between Executive Predictive Analytics vs Data Scientist?

AspectExecutive Predictive AnalyticsData Scientist
Required CredentialsOften requires advanced degrees in business, analytics, or related fields; certifications in analytics toolsTypically requires degrees in computer science, statistics, or mathematics; certifications in programming and data analysis
Work EnvironmentStrategic, executive-level settings; focuses on business impact and decision-makingTechnical environment; involves data modeling, coding, and statistical analysis
Employer & Industry UsageUsed in corporate strategy, finance, marketing, and operations departmentsEmployed across tech, finance, healthcare, and research organizations

While both roles involve data analysis and predictive modeling, Executive Predictive Analytics focuses on strategic insights for leadership decision-making, whereas Data Scientists handle technical data modeling and algorithm development. The roles often overlap but differ mainly in scope and target audience.

What are the most commonly searched types of Predictive Analytics jobs in California?

The most popular types of Predictive Analytics jobs in California are:

What cities in California are hiring for Executive Predictive Analytics jobs?

Cities in California with the most Executive Predictive Analytics job openings:

Executive Predictive Analytics jobs near you
Infographic showing various Executive Predictive Analytics job openings in California as of June 2026, with employment types broken down into 93% Full Time, 4% Part Time, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution.

Sr. Director, Enterprise Artificial Intelligence

International Executive Service Corps

Lake Forest, CA • On-site

$200 - $300/hr

Other

Posted 20 days ago

Job description

MAIN JOB RESPONSIBILITIES / COMPETENCIES

The Director, Enterprise Artificial Intelligence is responsible for leading the Company's enterprise Artificial Intelligence (AI) strategy and driving business transformation through the adoption of AI-enabled capabilities across the organization. This role partners closely with Executive Leadership, Manufacturing, Supply Chain, Engineering, Quality Assurance, Regulatory Affairs, Commercial Operations, Finance, Human Resources, Cybersecurity, Infrastructure, and Information Technology to identify, prioritize, and implement Artificial Intelligence solutions that improve operational efficiency, decision making, customer experience, innovation, and long-term competitive advantage.

This position provides strategic leadership for enterprise AI governance, Responsible AI, Generative AI, Agentic AI, Machine Learning, Intelligent Automation, and enterprise knowledge management while ensuring AI initiatives deliver measurable business value, align with corporate objectives, and support secure, scalable, and sustainable business transformation.

  • 1.Lead and execute the Company's enterprise Artificial Intelligence strategy aligned with corporate objectives, digital transformation initiatives, and measurable business outcomes.
  • 2.Establish and operationalize an Enterprise AI Center of Excellence (AI CoE) responsible for governance, standards, reusable AI capabilities, and enterprise adoption.
  • 3.Drive enterprise business transformation through the application of Artificial Intelligence, Generative AI, Agentic AI, Machine Learning, Predictive Analytics, and Intelligent Automation.
  • 4.Partner with executive leadership and business stakeholders to identify and prioritize AI initiatives that improve operational efficiency, product quality, customer experience, revenue growth, and employee productivity.
  • 5.Develop enterprise AI roadmaps, investment strategies, business cases, and value realization plans.
  • 6.Establish Responsible AI governance, AI policies, model lifecycle management, and AI risk management practices.
  • 7.Lead implementation of RAG, semantic search, vector databases, AI assistants, and enterprise knowledge management.
  • 8.Integrate AI with Oracle Fusion ERP, OCI, OIC, Salesforce, MES, PLM, enterprise data platforms, and cloud-native applications.
  • 9.Establish KPIs and executive dashboards measuring AI adoption and business value.
  • 10.Lead organizational change management and enterprise AI adoption.
  • 11.Recruit and mentor a team of AI/Business Engineers, Data Engineer/architects and AI Product Owner.
  • 12.Evaluate emerging AI technologies and strategic technology partnerships.
  • 13.Foster innovation, continuous improvement, and responsible AI adoption.
  • 14.Other duties as assigned.
REQUIREMENTS EDUCATION & TRAINING
  • Bachelor’s degree in computer science, Artificial Intelligence, Data Science, Engineering, Information Technology, Business Administration, or related discipline required or equivalent combination of education/experience.
  • Advanced degree preferred.
  • Professional certifications in AI, Cloud Computing, Enterprise Architecture, Cybersecurity, Project Management, or Data Analytics are highly desirable.
EXPERIENCE
  • 12+ years of progressive leadership experience in enterprise technology, digital transformation, Artificial Intelligence, data analytics, enterprise architecture, software engineering, or related disciplines.
  • 3+ years leading enterprise digital AI transformation organizations.
  • Demonstrated success developing enterprise AI strategies delivering measurable business transformation.
  • Experience with Generative AI, LLMs, Agentic AI, RAG, Machine Learning, Predictive Analytics, and Intelligent Automation.
  • Experience in integrating AI with ERP, CRM, Supply Chain, Manufacturing, Finance, HR, and enterprise platforms.
  • Experience presenting AI strategies and business outcomes to executive leadership and Boards.
  • Enterprise AI governance, organizational change management, and global business transformation.
  • FDA-regulated medical devices, biotechnology, pharmaceutical, life sciences, or other regulated industries preferred.
SKILLS
  • Strong knowledge of enterprise Artificial Intelligence strategy, governance, operating models, enterprise architecture, and business transformation methodologies, including the development of AI roadmaps, investment strategies, Centers of Excellence, and enterprise adoption frameworks.
  • Deep understanding of Generative AI, Large Language Models (LLMs), Agentic AI, Retrieval-Augmented Generation (RAG), prompt engineering, AI orchestration frameworks, semantic search, vector databases, AI assistants, autonomous agents, and intelligent automation technologies.
  • Strong understanding of Machine Learning, Predictive Analytics, Natural Language Processing (NLP), Computer Vision, AI model lifecycle management, model evaluation, MLOps, LLMOps, and enterprise AI platform operations.
  • Strong knowledge of enterprise cloud platforms including Oracle Cloud Infrastructure (OCI), Microsoft Azure, Amazon Web Services (AWS), Google Cloud Platform (GCP), cloud-native architectures, APIs, microservices, enterprise integration, event-driven architectures, and hybrid cloud environments.
  • Deep understanding of enterprise data architecture, data governance, master data management, metadata management, data quality, knowledge management, vector storage, and enterprise information management principles supporting AI-enabled decision making.
  • Strong understanding of Responsible AI principles, AI governance, cybersecurity, privacy, regulatory compliance, intellectual property protection, model transparency, explainability, AI ethics, enterprise risk management, and secure AI deployment practices.
  • Demonstrated ability to align Artificial Intelligence investments with corporate strategy by developing business cases, value realization frameworks, key performance indicators (KPIs), executive dashboards, and measurable financial and operational outcomes.
  • Ability to partner effectively with Executive Leadership, Information Technology, Manufacturing, Engineering, Supply Chain, Quality Assurance, Regulatory Affairs, Finance, Human Resources, Cybersecurity, Legal, and external technology partners to deliver enterprise-wide AI capabilities.
  • Excellent analytical, strategic planning, organizational, communication, executive presentation, negotiation, financial management, vendor management, stakeholder engagement, and organizational change management skills.
  • Demonstrated leadership building, mentoring, and scaling high-performing multidisciplinary teams consisting of AI Engineers, Data Scientists, Machine Learning Engineers, AI Solution Architects, Enterprise Architects, Product Managers, and business technology professionals.
  • Proven ability to lead enterprise modernization initiatives, drive innovation, establish AI governance, manage organizational change, and deliver measurable business transformation while maintaining secure, scalable, and responsible AI practices.

Pay range: $200K - $300K - Final compensation/salary will depend on experience.

STAAR Surgical is an Equal Employment Opportunity/Affirmative Action employer and all qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran or disability status, or any other characteristic protected by law #USA

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