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Executive Data Scientist Experimentation Jobs in Riverside, CA

TAE

Senior Scientist - Plasma Diagnostics

Foothill Ranch, CA · On-site

$94K - $129K/yr

You will also run experiments, perform data analysis, and translate raw diagnostic signals into physics-based insights. This is a full-lifecycle scientific role. We are not just looking for a ...

Vesync

Sr. Applied Behavioral Scientist

Tustin, CA · On-site

... data, causal inference and adaptive experimentation, and who is comfortable translating both into practical, sprint-compatible infrastructure at an industry pace. What you will do at VeSync: Just-in ...

Vesync

Sr. Applied Behavioral Scientist

Tustin, CA · On-site

... data, causal inference and adaptive experimentation, and who is comfortable translating both into practical, sprint-compatible infrastructure at an industry pace. What you will do at VeSync: Just-in ...

Vesync

Sr. Applied Behavioral Scientist

Tustin, CA · On-site

... data, causal inference and adaptive experimentation, and who is comfortable translating both into practical, sprint-compatible infrastructure at an industry pace. What you will do at VeSync: Just-in ...

Fujifilm

Director Data AI & Analytics

Irvine, CA · Hybrid

Deliver executive and operational analytics (FPY/yield, OEE, deviation/CAPA TAT, batch release, QC ... Lead data science programs for manufacturing quality, supply chain, and R&D. * Own bioinformatics ...

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All JobsData Scientist Experimentation JobsExecutive Data Scientist Experimentation JobsExecutive Data Scientist Experimentation Jobs in Riverside, CA

Executive Data Scientist Experimentation information

See Riverside, CA salary details

$39.1K

$128K

$205K

How much do executive data scientist experimentation jobs pay per year?

As of Sep 3, 2026, the average yearly pay for executive data scientist experimentation 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 is an executive data scientist experimentation?

An Executive Data Scientist Experimentation is a senior-level professional who leads and oversees the design, implementation, and analysis of experiments and data-driven initiatives within an organization. They are responsible for developing experimentation strategies, guiding teams in A/B testing, and ensuring that data insights drive business decisions. This role often collaborates with executive leadership to align data science projects with strategic goals and maximize business impact. Executive Data Scientists also mentor junior staff, set best practices, and ensure that experimentation methods are rigorous and ethical.

What are the key skills and qualifications needed to thrive as an executive data scientist experimentation?

To thrive as an Executive Data Scientist Experimentation, you need advanced expertise in statistics, experimental design, and data modeling, typically backed by a PhD or master's degree in a quantitative field. Mastery of tools such as Python, R, SQL, and platforms like AWS or Azure, along with experience in A/B testing and big data systems, is essential. Leadership, strategic thinking, and strong communication skills are crucial for guiding teams and translating complex data into actionable business insights. These skills and qualities are vital for driving data-driven decision-making and delivering impactful business results through rigorous experimentation.

How does an executive data scientist experimentation typically collaborate with cross-functional teams to drive business impact?

As an Executive Data Scientist focusing on experimentation, you will frequently partner with product managers, engineers, and business leaders to design and interpret experiments that inform strategic decisions. Your role involves translating business questions into measurable hypotheses, guiding teams on best practices for A/B testing, and ensuring rigorous analysis. Effective communication is key, as you'll need to present complex findings in a clear way that supports decision-making across the organization. This collaborative approach not only maximizes the impact of your data insights but also fosters a culture of evidence-based innovation.

What is the difference between Executive Data Scientist Experimentation vs Data Scientist Experimentation?

AspectExecutive Data Scientist ExperimentationData Scientist Experimentation
CredentialsAdvanced degrees (Master's/PhD), leadership experienceBachelor's or Master's in Data Science, Statistics, or related fields
Work EnvironmentStrategic planning, cross-department collaboration, leadership rolesData analysis, model development, experimentation execution
Employer & Industry UsageTech companies, finance, consulting firms with strategic focusTech, e-commerce, healthcare, and other data-driven industries

Executive Data Scientist Experimentation roles focus on strategic oversight, leadership, and aligning experimentation efforts with business goals. Data Scientist Experimentation roles are more hands-on, involving designing and executing experiments to analyze data and inform decisions. Both roles require strong analytical skills, but the executive level emphasizes leadership and strategic impact.

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Executive Data Scientist Experimentation jobs near you

Senior Data Scientist / ML Analytics / BI & Reporting / SQL / Python / Irvine CA

Motion Recruitment

Lake Forest, CA • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

This job post has expired today. Applications are no longer accepted.

Job description

Our client is a global leader in the iOT space for retail loss prevention, operations management, and analytics, with our headquarters based in South OC, California. They maintain a strong presence across the globe, with offices in the UK, Australia, China, Hong Kong, Germany, France, and Canada
They are urgently seeking a Sr. level Data Scientist & Analytics / ML Engineer with strong SQL, Python, Business Intelligence, Reporting Dashboars and Predictive Models.
This individual will play a key role in advancing the company’s analytics capabilities beyond traditional business intelligence by developing predictive models, operational analytics, customer intelligence frameworks, and scalable reporting solutions that support proactive decision-making and measurable business impact.
The ideal candidate combines strong technical and analytical expertise with the ability to understand business operations, communicate insights effectively, and partner cross-functionally to solve complex operational and customer challenges.
Role & Responsibilities
Customer & Operational Analytics:
  • Analyze customer, operational, monitoring, video classification, and theft-related data to identify trends, risks, opportunities, and actionable insights.
  • Develop analytical frameworks to measure customer utilization, operational effectiveness, subscription adoption, and customer value realization.
  • Support proactive customer engagement strategies through data-driven insights and trend analysis.
  • Partner with leadership teams to improve visibility into operational and customer performance metrics.
Predictive Modeling & Data Science:
  • Design, build, and maintain predictive models related to theft trends, customer behavior, operational risks, service utilization, and escalation indicators.
  • Develop forecasting and trend analysis models that support operational planning and customer success initiatives.
  • Apply statistical analysis, machine learning, and advanced analytics techniques where appropriate to improve business outcomes.
  • Continuously evaluate and refine model performance and business relevance.
Business Intelligence & Visualization:
  • Develop dashboards, KPI reporting, and analytics tools using Power BI, Tableau, or similar platforms.
  • Create executive-level reporting and operational scorecards that support strategic decision-making.
  • Automate reporting and improve scalability of analytics and data visualization capabilities.
  • Translate complex analytical findings into clear, business-oriented recommendations.
Cross-Functional Collaboration:
  • Partner closely with Operations, Customer Success, Sales, Product Management, IT, Engineering, and Finance teams to identify business opportunities and analytics priorities.
  • Support initiatives involving AI-driven analytics, workflow automation, and operational optimization.
  • Collaborate with technical teams to improve data quality, accessibility, integration, and governance across systems and platforms.
Must Have Skills:
  • Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Business Analytics, or related field.
  • 4-8 years of experience in data science, predictive analytics, customer analytics, operational analytics, or related analytical roles.
  • Strong experience developing predictive models and performing advanced data analysis in business environments.
  • Advanced proficiency in SQL and experience with Python or similar analytics/programming languages.
  • Experience with Power BI, Tableau, or similar business intelligence and visualization tools.
  • Experience working with large, complex operational and customer datasets.
  • Strong analytical, problem-solving, and critical-thinking capabilities.
  • Excellent communication and presentation skills with the ability to explain technical concepts to business stakeholders.
  • Ability to operate independently and manage multiple priorities in a fast-paced environment.
  • Education And/Or Experience : BSEE, MSEE, BSCS, or MSCS
Nice to have / Preferred Skills:
  • Experience in SaaS, retail technology, video analytics, loss prevention, IoT, subscription-based services, or service-oriented organizations.
  • Familiarity with machine learning, AI-driven analytics, and operational optimization techniques.
  • Experience with cloud-based data platforms such as Azure, AWS, or Google Cloud.
  • Experience supporting executive-level operational reporting and KPI development.
The Offer
  • Attractive total compensation package between 130-160k
  • Comprehensive healthcare benefits including medical, dental, and vision coverage; Life/ADD/LTD insurance; FSA/HSA options
  • 401(k) Plan with employer match
  • Generous paid time off policy
  • Observance of 11 paid company holidays

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