Data Science Vice President
Company Description
The company is a forward-thinking organization focused on leveraging data to drive strategic decision-making and innovation. It invests in modern data infrastructure and advanced analytics to unlock value across all business functions. Team members collaborate across disciplines to build scalable, data-driven solutions that improve performance and customer outcomes. The culture emphasizes accountability, measurable impact, and continuous improvement in how data is collected, analyzed, and used. Role Description The Data Science Vice President is a full-time remote role responsible for leading the organization’s data science vision, strategy, and execution. This role oversees data science teams, sets priorities, and ensures delivery of high-impact analytical solutions that support business goals. Day-to-day responsibilities include defining data science roadmaps, reviewing models and methodologies, guiding experiment design, and ensuring the quality and reliability of analytical outputs. The Data Science Vice President collaborates closely with executive leadership, product, engineering, and operations to identify opportunities where data science can improve outcomes and efficiency. This role also establishes best practices, mentors senior data professionals, and promotes a culture of ethical, responsible, and transparent use of data and algorithms.
Qualifications
Strong Analytical Skills and expertise in Data Analytics to interpret complex data sets and inform strategic decisions. Advanced proficiency in Data Science and Statistics to design, build, and validate predictive and prescriptive models. Experience with Pattern Recognition and related methods to identify trends, anomalies, and actionable insights in large-scale data. Proven leadership experience managing senior data science teams and large, cross-functional analytical initiatives. Hands-on knowledge of modern data science tools, programming languages (such as Python or R), and machine learning frameworks. Familiarity with data engineering concepts, data pipelines, and cloud-based analytics platforms. Excellent communication skills to translate technical concepts into clear, actionable recommendations for non-technical stakeholders. Track record of driving measurable business impact through data-driven strategies and experimentation. Commitment to ethical AI practices, data privacy, and regulatory compliance. Advanced degree (Master’s or PhD) in Data Science, Statistics, Computer Science, Mathematics, or a related quantitative field, or equivalent experience.