Chief Data Officer (CDO)
J
JobgetherTechnology
Based in the United StatesFull-TimeExecutive
Salary not disclosed
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Job Details
- Experience
- 10+ years
- Required Skills
- LeadershipArtificial IntelligenceMachine LearningA/B testingMLOps
Requirements
- Proven experience as a Chief Data Officer, VP of Data, VP of Analytics, or similar senior data leadership role.
- 10+ years of progressive experience in data, analytics, machine learning, or technology leadership roles, including experience building and scaling teams.
- Strong hands-on expertise in machine learning and AI, including experience designing, training, evaluating, and improving models.
- Demonstrated experience creating and managing A/B testing or experimentation frameworks to support data-driven decisions.
- Proven ability to translate data strategies into measurable business outcomes, ideally connected to revenue growth, customer value, or monetization improvements.
- Deep understanding of modern data architecture, cloud data platforms, pipelines, MLOps, and enterprise data infrastructure.
- Experience establishing data governance, security, privacy, and compliance frameworks.
- Strong executive communication skills with the ability to influence senior stakeholders, leadership teams, and cross-functional partners.
- Bachelor's degree in a quantitative discipline such as Computer Science, Statistics, Data Science, Engineering, or a related field; advanced degree preferred.
- Experience in gaming, payments, monetization, technology platforms, or other data-intensive industries is highly desirable.
Responsibilities
- Define, own, and execute an enterprise-wide data strategy aligned with business objectives and measurable growth outcomes.
- Translate data vision into action by building teams, roadmaps, infrastructure, and operating models that turn data into a strategic advantage.
- Partner with product, engineering, marketing, and business teams to identify opportunities where analytics, AI, and machine learning can improve customer value and revenue performance.
- Personally guide the development, evaluation, and optimization of machine learning and AI models, ensuring solutions deliver measurable impact.
- Design and establish experimentation frameworks, including A/B testing methodologies, statistical standards, and decision-making processes for scaling successful initiatives.
- Lead data governance, quality, security, and privacy practices while ensuring compliance with applicable regulations and internal standards.
- Build and scale a high-performing data organization across data science, analytics engineering, and machine learning functions.
- Recruit, mentor, and develop data professionals while establishing technical excellence and career growth frameworks.
- Break down organizational data silos and promote a strong data-driven culture across executive and cross-functional teams.
- Report on data strategy progress, model performance, experimentation results, and business impact to senior leadership.
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