Data Science Vice President

Company Description The company is a data-driven organization that leverages advanced analytics and data science to inform strategic decisions and drive growth. It invests in modern data infrastructure, cloud technologies, and scalable platforms to support innovation and experimentation. Cross-functional collaboration is central to how the organization operates, with data teams partnering closely with product, engineering, operations, and business stakeholders. The company values ethical data use, transparency, and measurable impact from its analytics and data science initiatives.
Role Description The Data Science Vice President is a full-time, remote leadership role responsible for setting the strategic vision for data science across the organization. This role oversees the design, development, and deployment of advanced analytics, machine learning models, and data products that support key business objectives. Day-to-day activities include managing and mentoring data science teams, prioritizing project portfolios, establishing standards for experimentation and model governance, and collaborating with senior leadership to identify high-impact opportunities. The Data Science Vice President will also work closely with data engineering and analytics teams to ensure robust data pipelines, high-quality datasets, and consistent reporting frameworks. Regular responsibilities include presenting insights to executives, aligning data science initiatives with business strategy, and fostering a culture of innovation, collaboration, and continuous improvement.
Qualifications
Strong foundation in Data Science and Statistics, including experience with statistical modeling, machine learning, and experimental design.
Advanced Analytical Skills and Data Analytics experience, with the ability to translate complex data into clear, actionable insights for non-technical stakeholders.
Expertise in Pattern Recognition and predictive modeling, including familiarity with algorithms for classification, clustering, and anomaly detection.
Demonstrated experience leading and scaling data science teams, including hiring, mentoring, and performance management.
Proficiency with common data science tools and languages (e.g., Python or R, SQL, and relevant ML frameworks), and understanding of cloud-based data platforms.
Proven track record of delivering data science solutions that drive measurable business outcomes and inform executive decision-making.
Excellent communication and stakeholder management skills, with the ability to influence at the executive level and collaborate across functions.
Master’s or PhD in a quantitative field (e.g., Computer Science, Statistics, Mathematics, Engineering, Data Science) or equivalent practical experience.
Experience establishing data governance, model risk management, and ethical AI practices is highly beneficial.

Work arrangement
Yes