Data Science Vice President

Company Description
LEHNER INVESTMENTS is an investment firm focused on leveraging data-driven strategies to support informed decision-making and sustainable growth. The organization integrates quantitative analysis, technology, and market expertise to identify opportunities across asset classes. LEHNER INVESTMENTS values innovation, rigorous research, and collaboration across multidisciplinary teams. Joining the company offers the opportunity to shape data strategy in a dynamic environment and contribute to the advancement of modern investment approaches.
Role Description
The Data Science Vice President is a full-time remote role responsible for leading the data science function and driving advanced analytics initiatives across the organization. This role oversees the design, development, and deployment of data models, predictive analytics, and pattern recognition solutions that inform investment strategies and business decisions. Day-to-day activities include guiding a team of data professionals, setting technical direction, reviewing methodologies, and ensuring the quality, accuracy, and scalability of analytical outputs. The Vice President collaborates closely with senior leadership, portfolio managers, and technology stakeholders to translate business needs into data-driven solutions, prioritize projects, and implement best practices in data governance and model validation. This role also evaluates new tools, techniques, and data sources to enhance the firm’s analytical capabilities and maintain a culture of continuous improvement.
Qualifications
Strong Analytical Skills with demonstrated ability to frame complex problems, interpret results, and communicate insights clearly.
Advanced expertise in Data Science, including model development, machine learning techniques, and end-to-end solution deployment.
Solid foundation in Statistics for experimental design, hypothesis testing, and rigorous model evaluation.
Experience with Data Analytics and Pattern Recognition to identify trends, anomalies, and actionable signals from large datasets.
Proficiency in relevant programming languages and tools (e.g., Python, R, SQL, distributed computing frameworks, data visualization platforms).
Proven leadership experience in managing and mentoring data science or analytics teams, including setting strategic direction and performance standards.
Background in finance, investments, or a related quantitative field is highly beneficial, with ability to connect analytical work to business outcomes.
Advanced degree in a quantitative discipline (e.g., Data Science, Computer Science, Mathematics, Statistics, Engineering, Economics) or equivalent practical experience.
Strong communication and stakeholder management skills, with ability to collaborate effectively in a remote environment and across diverse teams.
Commitment to ethical data use, robust model governance, and continuous learning in emerging data science methodologies and technologies.

Work arrangement
Yes